From 16664145ec07ba3df7e6baa9e91b54b20022999f Mon Sep 17 00:00:00 2001 From: Sasha Date: Mon, 18 Nov 2024 11:11:26 -0500 Subject: [PATCH] update --- _data/members.yaml | 10 + _data/papers.yaml | 1237 +++++++++++++++++++++++--------------------- _site/css/main.css | 730 ++++++++++---------------- cv/cv.comp.pdf | Bin 130650 -> 131486 bytes cv/cv.comp.tex | 638 ++++++++++++----------- cv/cv.tex | 361 +++++++------ cv/make.sh | 6 +- index.html | 22 +- papers.html | 352 +++++++++---- 9 files changed, 1689 insertions(+), 1667 deletions(-) diff --git a/_data/members.yaml b/_data/members.yaml index 98224ba..ceca457 100644 --- a/_data/members.yaml +++ b/_data/members.yaml @@ -18,6 +18,16 @@ github: celine-lee githubid: 22714518 title : PhD Student + - name : Shankar Padmanabhan + email: + title: PhD Student + url: "https://shankarp8.github.io/" + githubid: 47063867 + - name : Daniel Ritter + email: + title: PhD Student + url: "https://danieldritter.github.io/" + githubid: 35882844 - name : Junxiong Wang email: junxiong@cs.cornell.edu title: PhD Student diff --git a/_data/papers.yaml b/_data/papers.yaml index 36dc7d2..64d8aba 100644 --- a/_data/papers.yaml +++ b/_data/papers.yaml @@ -1,624 +1,669 @@ -notable: - - title: "Zephyr: Direct Distillation of LM Alignment" - authors: "Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, Thomas Wolf" - pdf: "https://arxiv.org/pdf/2310.16944.pdf" - conference: COLM 2024 - image: - - title: "Pretraining Without Attention" - authors: "Junxiong Wang, Jing Nathan Yan, Albert Gu, Alexander M. Rush" - pdf: "https://arxiv.org/pdf/2212.10544.pdf" - conference: EMNLP 2023 Findings - image: /images/bigs.png - - title: "Multitask prompted training enables zero-shot task generalization" - authors: Victor Sanh, et al. - pdf: https://arxiv.org/pdf/2110.08207 - image: "https://github.com/bigscience-workshop/promptsource/raw/main/assets/promptsource_app.png" - conference: ICLR 2022 - - title: "How many data points is a prompt worth?" - authors: Teven Le Scao, Alexander M. Rush - pdf: https://aclanthology.org/2021.naacl-main.208.pdf - image: /images/prompt.png - conference: NAACL Short 2021 - - title: "Transformers: State-of-the-art Natural Language Processing" - authors: Thomas Wolf et al - pdf: https://arxiv.org/pdf/1910.03771 - image: /images/transformers.png - conference: EMNLP Demos 2020 - - title: "Compound Probabilistic Context-Free Grammars for Grammar Induction" - authors: Yoon Kim, Chris Dyer, Alexander M. Rush - pdf: https://www.aclweb.org/anthology/P19-1228/ - code: https://github.com/harvardnlp/compound-pcfg - image: /images/Tree.png - conference: ACL 2019 - - title: "Learning Neural Templates for Text Generation" - authors: Sam Wiseman, Stuart M. Shieber, Alexander Rush - conference: EMNLP 2018 - code: https://github.com/harvardnlp/neural-template-gen - pdf : https://arxiv.org/abs/1808.10122 - image: /images/template.png - - title: "LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks" - authors: Hendrik Strobelt, Sebastian Gehrmann, Hanspeter Pfister, and Alexander M. Rush - conference: InfoVis 2017 - pdf : http://lstm.seas.harvard.edu/ - code : http://lstm.seas.harvard.edu/ - image: /images/small_teaser.png - - title: "OpenNMT: Open-Source Toolkit for Neural Machine Translation" - authors: Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush - conference: ACL Demo 2017 - pdf : https://arxiv.org/abs/1701.02810 - image: /images/overview.png - slides: - - title: Sequence-Level Knowledge Distillation - authors: Yoon Kim and Alexander M. Rush - conference: EMNLP 2016 - pdf : http://arxiv.org/pdf/1606.07947v1.pdf - image: /images/segknow.png - slides : /slides/emnlp16_seqkd.pdf - code: https://github.com/harvardnlp/seq2seq-attn - - title: Character-Aware Neural Language Models - authors : Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush - conference : AAAI 2016 - code : https://github.com/yoonkim/lstm-char-cnn - pdf : https://arxiv.org/pdf/1508.06615v4 - slides : /slides/aaai16.pdf - image : /images/charrnn.png - - title: A Neural Attention Model for Abstractive Sentence Summarization - authors : Alexander M. Rush, Sumit Chopra, and Jason Weston - conference : EMNLP 2015. - pdf : http://arxiv.org/pdf/1509.00685.pdf - code : https://github.com/facebook/NAMAS - slides : /slides/emnlp15.pdf - image : /images/summary.png +notable: + - title: "Simple and Effective Masked Diffusion Language Models" + authors: "Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T Chiu, Alexander Rush, Volodymyr Kuleshov" + pdf: "https://arxiv.org/abs/2406.07524" + image: /images/diffusion.png + conference: NeurIPS 2024 + - title: "Zephyr: Direct Distillation of LM Alignment" + authors: "Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, Thomas Wolf" + pdf: "https://arxiv.org/pdf/2310.16944.pdf" + conference: COLM 2024 + image: + - title: "Pretraining Without Attention" + authors: "Junxiong Wang, Jing Nathan Yan, Albert Gu, Alexander M. Rush" + pdf: "https://arxiv.org/pdf/2212.10544.pdf" + conference: EMNLP 2023 Findings + image: /images/bigs.png + - title: "Multitask prompted training enables zero-shot task generalization" + authors: Victor Sanh, et al. + pdf: https://arxiv.org/pdf/2110.08207 + image: "https://github.com/bigscience-workshop/promptsource/raw/main/assets/promptsource_app.png" + conference: ICLR 2022 + - title: "How many data points is a prompt worth?" + authors: Teven Le Scao, Alexander M. Rush + pdf: https://aclanthology.org/2021.naacl-main.208.pdf + image: /images/prompt.png + conference: NAACL Short 2021 + - title: "Transformers: State-of-the-art Natural Language Processing" + authors: Thomas Wolf et al + pdf: https://arxiv.org/pdf/1910.03771 + image: /images/transformers.png + conference: EMNLP Demos 2020 + - title: "Compound Probabilistic Context-Free Grammars for Grammar Induction" + authors: Yoon Kim, Chris Dyer, Alexander M. Rush + pdf: https://www.aclweb.org/anthology/P19-1228/ + code: https://github.com/harvardnlp/compound-pcfg + image: /images/Tree.png + conference: ACL 2019 + - title: "Learning Neural Templates for Text Generation" + authors: Sam Wiseman, Stuart M. Shieber, Alexander Rush + conference: EMNLP 2018 + code: https://github.com/harvardnlp/neural-template-gen + pdf: https://arxiv.org/abs/1808.10122 + image: /images/template.png + - title: "LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks" + authors: Hendrik Strobelt, Sebastian Gehrmann, Hanspeter Pfister, and Alexander M. Rush + conference: InfoVis 2017 + pdf: http://lstm.seas.harvard.edu/ + code: http://lstm.seas.harvard.edu/ + image: /images/small_teaser.png + - title: "OpenNMT: Open-Source Toolkit for Neural Machine Translation" + authors: Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush + conference: ACL Demo 2017 + pdf: https://arxiv.org/abs/1701.02810 + image: /images/overview.png + slides: + - title: Sequence-Level Knowledge Distillation + authors: Yoon Kim and Alexander M. Rush + conference: EMNLP 2016 + pdf: http://arxiv.org/pdf/1606.07947v1.pdf + image: /images/segknow.png + slides: /slides/emnlp16_seqkd.pdf + code: https://github.com/harvardnlp/seq2seq-attn + - title: Character-Aware Neural Language Models + authors: Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush + conference: AAAI 2016 + code: https://github.com/yoonkim/lstm-char-cnn + pdf: https://arxiv.org/pdf/1508.06615v4 + slides: /slides/aaai16.pdf + image: /images/charrnn.png + - title: A Neural Attention Model for Abstractive Sentence Summarization + authors: Alexander M. Rush, Sumit Chopra, and Jason Weston + conference: EMNLP 2015. + pdf: http://arxiv.org/pdf/1509.00685.pdf + code: https://github.com/facebook/NAMAS + slides: /slides/emnlp15.pdf + image: /images/summary.png papers: - - title: "MambaByte: Token-free Selective State Space Model" - authors: "Junxiong Wang, Tushaar Gangavarapu, Jing Nathan Yan, Alexander M. Rush" - pdf: https://arxiv.org/abs/2401.13660 - conference: COLM 2024 - - title: "Zephyr: Direct Distillation of LM Alignment" - authors: "Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, Thomas Wolf" - pdf: "https://arxiv.org/pdf/2310.16944.pdf" - conference: COLM 2024 - image: - - title: "Guess and Sketch: Language Model Guided Transpilation" - authors: "Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander M. Rush" - pdf: "https://arxiv.org/pdf/2309.14396.pdf" - conference: ICLR 2024 - image: - - title: "Symbolic Planning and Code Generation for Grounded Dialogue" - authors: "Justin T. Chiu, Wenting Zhao, Derek Chen, Saujas Vaduguru, Alexander M. Rush, Daniel Fried" - pdf: "https://arxiv.org/pdf/2310.17140.pdf" - conference: EMNLP 2023 - image: - - title: "Teal: Learning-Accelerated Optimization of WAN Traffic Engineering" - authors: "Zhiying Xu, Francis Y. Yan, Rachee Singh, Justin T. Chiu, Alexander M. Rush, Minlan Yu" - pdf: "https://arxiv.org/abs/2210.13763" - conference: "SIGCOMM 2023" - image: - - title: "Text Embeddings Reveal (Almost) As Much As Text" - authors: "John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov, Alexander M. Rush" - pdf: "https://arxiv.org/pdf/2310.06816.pdf" - conference: EMNLP 2023 - image: - - title: "Tree Prompting: Efficient Task Adaptation without Fine-Tuning" - authors: "John X. Morris, Chandan Singh, Alexander M. Rush, Jianfeng Gao, Yuntian Deng" - pdf: "https://arxiv.org/pdf/2310.14034.pdf" - conference: EMNLP 2023 - image: - - title: "HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervision" - authors: "Wenting Zhao, Justin T. Chiu, Claire Cardie, Alexander M. Rush" - pdf: "https://arxiv.org/pdf/2305.14237.pdf" - conference: EMNLP 2023 - image: - - title: "Pretraining Without Attention" - authors: "Junxiong Wang, Jing Nathan Yan, Albert Gu, Alexander M. Rush" - pdf: "https://arxiv.org/pdf/2212.10544.pdf" - conference: EMNLP 2023 Findings - image: /images/bigs.png - - title: "Scaling Data-Constrained Language Models" - authors: "Niklas Muennighoff, Alexander M. Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, Colin Raffel" - pdf: "https://arxiv.org/pdf/2305.16264.pdf" - conference: NeurIPS 2023 (Oral) - image: - - title: "OBELISC: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents" - authors: "Hugo Laurençon, Lucile Saulnier, Léo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov, Thomas Wang, Siddharth Karamcheti, Alexander M. Rush, Douwe Kiela, Matthieu Cord, Victor Sanh" - pdf: "https://arxiv.org/pdf/2306.16527.pdf" - conference: NeurIPS 2023 Dataset - image: "" - - title: "Abductive Commonsense Reasoning Exploiting Mutually Exclusive Explanations" - authors: "Wenting Zhao, Justin T. Chiu, Claire Cardie, Alexander M. Rush" - pdf: "https://arxiv.org/pdf/2305.14618.pdf" - conference: "ACL 2023" - image: "" - - title: "Markup-to-Image Diffusion Models with Scheduled Sampling" - authors: "Yuntian Deng, Noriyuki Kojima, Alexander M. Rush" - pdf: "https://arxiv.org/abs/2210.05147" - conference: "ICLR 2023" - image: "" - - title: "A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management" - authors: "Thierry Tambe, Jeff Zhang, Coleman Hooper, Tianyu Jia, Paul N. Whatmough, Joseph Zuckerman, Maico Cassel dos Santos, Erik Jens Loscalzo, Davide Giri, Kenneth L. Shepard, Luca P. Carloni, Alexander M. Rush, David Brooks, Gu-Yeon Wei" - pdf: - conference: "ISSCC 2023" - image: "" - - title: "BLOOM: A 176B-Parameter Open-Access Multilingual Language Model" - authors: BigScience Workshop - pdf: https://arxiv.org/abs/2211.05100 - conference: Arxiv Preprint - - title: "Named Tensor Notation" - authors: David Chiang, Alexander M. Rush, Boaz Barak - pdf: https://arxiv.org/pdf/2102.13196.pdf - image: /images/ntn.png - conference: TMLR 2022 - - title: "Xatu: boosting existing DDoS detection systems using auxiliary signals" - authors: Zhiying Xu, Sivaramakrishnan Ramanathan, Alexander Rush, Jelena Mirkovic, Minlan Yu - pdf: https://dl.acm.org/doi/abs/10.1145/3555050.3569121 - image: /images/xatu.png - conference: CoNEXT 2022 - - title: "Unsupervised Text Deidentification" - authors: John X Morris, Justin T Chiu, Ramin Zabih, Alexander M Rush - pdf: https://arxiv.org/pdf/2210.11528.pdf - image: /images/deid.png - conference: EMNLP Findings 2022 - - title: "Model Criticism for Long-Form Text Generation" - authors: Yuntian Deng, Volodymyr Kuleshov, Alexander M Rush - pdf: https://arxiv.org/pdf/2210.08444.pdf - image: /images/modcrit.png - conference: EMNLP 2022 - - title: "Evaluate and Evaluation on the Hub: Better Best Practices for Data and Model Measurement" - authors: Leandro von Werra et al. - pdf: https://arxiv.org/abs/2210.01970 - image: /images/evalhub.png - conference: EMNLP Demos 2022 (Best Demo) - - title: "Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models" - authors: Hendik Strobelt et al. - pdf: https://ieeexplore.ieee.org/abstract/document/9908590 - image: - conference: IEEE Trans on Visualization 2022 - - title: "A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs" - authors: Thierry Tambe et al. - pdf: https://discovery.ucl.ac.uk/id/eprint/10150658/1/A_16-nm_SoC_for_Noise-Robust_Speech.pdf - image: /images/soundsource.png - conference: IEEE Solid-State Circuits 2022 - - title: "Promptsource: An integrated development environment and repository for natural language prompts" - authors: Stephen Bach et al. - pdf: https://arxiv.org/abs/2202.01279 - image: "https://github.com/bigscience-workshop/promptsource/raw/main/assets/promptsource_app.png" - conference: ACL Demo 2022 - - title: "End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman" - authors: Samantha Petti, et al. - pdf: http://repository.cshl.edu/id/eprint/40409/1/2021.Petti.multiple_sequence_alignments.pdf - image: "https://pbs.twimg.com/media/FCfRXOJXEAITHZ0?format=jpg&name=large" - conference: Bioinformatics - - title: "Multitask prompted training enables zero-shot task generalization" - authors: Victor Sanh, et al. - pdf: https://arxiv.org/pdf/2110.08207 - image: "https://github.com/bigscience-workshop/promptsource/raw/main/assets/promptsource_app.png" - conference: ICLR 2022 - - title: "Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field" - authors: Stanislav Lukyanenko et al. - pdf: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526069/ - image: - conference: MICCAI 2021 - - title: "Rationales for sequential predictions" - authors: Keyon Vafa, Yuntian Deng, David Blei, Alexander Rush - pdf: https://arxiv.org/pdf/2109.06387 - image: /images/seqrat.png - conference: EMNLP 2021 - - title: "Low-Rank Constraints for Fast Inference in Structured Models" - authors: Justin Chiu, Yuntian Deng, and Alexander M. Rush - pdf: "https://proceedings.neurips.cc/paper/2021/file/16c0d78ef6a76b5c247113a4c9514059-Paper.pdf" - image: - conference: NeurIPS 2021 - - title: "Conference demographics and footprint changed by virtual platforms" - authors: Matthe Skiles et al. - pdf: https://www.nature.com/articles/s41893-021-00823-2 - image: https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41893-021-00823-2/MediaObjects/41893_2021_823_Fig1_HTML.png?as=webp - conference: Nature Sustainability - - title: "Sequence-to-Lattice Models for Fast Translation" - authors: Yuntian Deng and Alexander M. Rush - pdf: https://aclanthology.org/2021.findings-emnlp.318.pdf - image: "https://github.com/harvardnlp/cascaded-generation/raw/master/cascaded-generation-fastest.gif" - conference: EMNLP Findings Short 2021 - - title: "Datasets: A Community Library for Natural Language Processing" - authors: Quentin Lhoest et al - pdf: https://arxiv.org/pdf/2109.02846.pdf - image: "https://huggingface.co/docs/datasets/_images/datasets_logo.png" - conference: EMNLP Demos 2021 (Best Demo) - - title: "EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference" - authors: Thierry Tambe and Others - pdf: https://arxiv.org/pdf/2011.14203.pdf - image: /images/edgebert.png - conference: IEEE MICRO 2021 - - title: "GenNI: Human-AI Collaboration for Data-Backed Text Generation" - authors: Hendrik Strobelt, Jambay Kinley, Robert Krueger, Johanna Beyer, Alexander M. Rush, Hanspeter Pfister - pdf: - image: /images/genni.png - conference: IEEE VIS 2021 - - title: "Parameter-efficient transfer learning with diff pruning" - authors: Demi Guo, Alexander M. Rush, Yoon Kim - pdf: https://arxiv.org/pdf/2012.07463.pdf - image: /images/diffprune.png - conference: ACL 2021 - - title: "How many data points is a prompt worth?" - authors: Teven Le Scao, Alexander M. Rush - pdf: https://aclanthology.org/2021.naacl-main.208.pdf - image: /images/prompt.png - conference: NAACL Short 2021 (Best Paper - Runner-Up) - - title: "Block pruning for faster transformers" - authors: François Lagunas, Ella Charlaix, Victor Sanh, Alexander M Rush - pdf: https://arxiv.org/pdf/2109.04838 - image: - conference: ACL 2021 - - title: "Low-Complexity Probing via Finding Subnetworks" - authors: Steven Cao, Victor Sanh, Alexander M. Rush - pdf: https://aclanthology.org/2021.naacl-main.74/ - image: /images/probing.png - conference: NAACL Short 2021 - - title: "Template Filling with Generative Transformers" - authors: Xinya Du, Alexander M. Rush, Claire Cardie - pdf: https://aclanthology.org/2021.naacl-main.70/ - image: - conference: NAACL Short 2021 - - title: "9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET" - authors: Thierry Tambe, En-Yu Yang, Glenn G Ko, Yuji Chai, Coleman Hooper, Marco Donato, Paul N Whatmough, Alexander M Rush, David Brooks, Gu-Yeon Wei - pdf: https://ieeexplore.ieee.org/abstract/document/9366062 - image: - conference: IEEE International Solid-State Circuits Conference 2021 - - title: "Cascaded Text Generation with Markov Transformers" - authors: Yuntian Deng, Alexander M. Rush - pdf: https://arxiv.org/pdf/2006.01112 - image: /images/cascade.png - conference: NeurIPS 2020 - - title: "Latent Template Induction with Gumbel-CRFs" - authors: Yao Fu, Chuanqi Tan, Bin Bi, Mosha Chen, Yansong Feng, Alexander Rush - pdf: https://github.com/FranxYao/Gumbel-CRF - image: https://raw.githubusercontent.com/FranxYao/Gumbel-CRF/main/img/model_github.png - conference: NeurIPS 2020 - - title: "Movement Pruning: Adaptive Sparsity by Fine-Tuning" - authors: Victor Sanh, Thomas Wolf, Alexander M. Rush - pdf: https://arxiv.org/pdf/2005.07683 - image: /images/movement.png - conference: NeurIPS 2020 - - title: "Scaling Hidden Markov Language Models" - authors: Justin T. Chiu, Alexander M. Rush - pdf: https://arxiv.org/abs/2011.04640 - image: /images/hmm.png - conference: EMNLP 2020 - - title: "Adversarial Semantic Collisions" - authors: Congzheng Song, Alexander M. Rush, Vitaly Shmatikov - pdf: https://www.cs.cornell.edu/~shmat/shmat_emnlp20.pdf - image: /images/shmat_emnlp20.png - conference: EMNLP 2020 - - title: "Sequence-Level Mixed Sample Data Augmentation" - authors: Demi Guo, Yoon Kim, Alexander M. Rush - pdf: https://www.aclweb.org/anthology/2020.emnlp-main.447/ - image: - conference: EMNLP 2020 - - title: "AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference" - authors: Thierry Tambe, En-Yu Yang, Zishen Wan, Yuntian Deng, Vijay Janapa Reddi, Alexander Rush, David Brooks, Gu-Yeon Wei - pdf: https://arxiv.org/pdf/1909.13271 - image: /images/adapt.png - conference: DAC 2020 (Best Paper) - - title: "Transformers: State-of-the-art Natural Language Processing" - authors: Thomas Wolf et al - pdf: https://arxiv.org/pdf/1910.03771 - image: /images/transformers.png - conference: EMNLP Demos 2020 (Best Demo) - - title: "Torch-Struct: Deep Structured Prediction Library" - authors: Alexander Rush - pdf: https://arxiv.org/pdf/2002.00876 - image: https://github.com/harvardnlp/pytorch-struct/raw/master/download.png - conference: ACL Demos 2020 (Best Demo Honorable Mention) - - title: "What is Learned in Visually Grounded Neural Syntax Acquisition" - authors: Noriyuki Kojima, Hadar Averbuch-Elor, Alexander M. Rush, Yoav Artzi - pdf: https://arxiv.org/pdf/2005.01678 - image: /images/learned.png - conference: ACL 2020 (Short) - - title: "Posterior Control of Blackbox Generation" - authors: Xiang Lisa Li, Alexander M. Rush - pdf: https://arxiv.org/pdf/2005.04560 - image: /images/posterior.png - conference: ACL 2020 - - title: "Automating Botnet Detection with Graph Neural Networks" - authors: Jiawei Zhou, Zhiying Xu, Alexander M. Rush, Minlan Yu - pdf: https://arxiv.org/pdf/2003.06344 - image: /images/botnet.png - conference: AutoML for Networking and Systems Workshop - - title: "LAN -- A materials notation for 2D layered assemblies" - authors: Georgios A. Tritsaris, Yiqi Xie, Alexander M. Rush, Stephen Carr, Marios Mattheakis, Efthimios Kaxiras - pdf: https://arxiv.org/pdf/1910.03413 - image: /images/lan.png - conference: - - title: "MASR: A Modular Accelerator for Sparse RNNs" - authors: Udit Gupta, Brandon Reagen, Lillian Pentecost, Marco Donato, Thierry Tambe, Alexander M. Rush, Gu-Yeon Wei, David Brooks - pdf: - image: /images/MASR.png - conference: PACT 2019 - - title: "Commonsense Knowledge Mining from Pretrained Models" - authors: "Joe Davison, Joshua Feldman and Alexander Rush" - pdf: - conference: EMNLP 2019 - - title: "Neural Linguistic Steganography" - authors: Zachary Ziegler, Yuntian Deng and Alexander Rush - pdf: https://arxiv.org/abs/1909.01496 - conference: EMNLP 2019 - - title: "Compound Probabilistic Context-Free Grammars for Grammar Induction" - authors: Yoon Kim, Chris Dyer, Alexander M. Rush - pdf: https://www.aclweb.org/anthology/P19-1228/ - code: https://github.com/harvardnlp/compound-pcfg - image: /images/Tree.png - conference: ACL 2019 + - title: "Compute-Constrained Data Selection" + authors: "J. O. Yin, Alexander Rush" + pdf: "https://arxiv.org/abs/2410.16208" + conference: Preprint 2024 + - title: "Contextual Document Embeddings" + authors: "J. X. Morris, Alexander Rush" + pdf: "https://arxiv.org/abs/2410.02525" + conference: Preprint 2024 + - title: "A controlled study on long context extension and generalization in llms" + authors: "Y. Lu, J. N. Yan, S. Yang, J. T. Chiu, S. Ren, F. Yuan, W. Zhao, Z. Wu, Alexander Rush" + pdf: "https://arxiv.org/abs/2409.12181" + conference: Preprint 2024 + - title: "The mamba in the llama: Distilling and accelerating hybrid models" + authors: "J. Wang, D. Paliotta, A. May, Alexander Rush, T. Dao" + pdf: "https://arxiv.org/abs/2408.15237" + conference: NeurIPS 2024 + - title: "Great Memory, Shallow Reasoning: Limits of NN-LMs" + authors: "S. Geng, W. Zhao, Alexander Rush" + pdf: "https://arxiv.org/abs/2408.11815" + conference: Preprint 2024 + - title: "Predicting text preference via structured comparative reasoning" + authors: "J. N. Yan, T. Liu, J. Chiu, J. Shen, Z. Qin, Y. Yu, C. Lakshmanan, Y. Kurzion, Alexander Rush" + pdf: "https://aclanthology.org/2024.acl-long.839/" + conference: ACL 2024 + - title: "I Could've Asked That: Reformulating Unanswerable Questions" + authors: "W. Zhao, G. Gao, C. Cardie, Alexander Rush" + pdf: "https://arxiv.org/abs/2407.17469" + conference: EMNLP 2024 + - title: "ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models" + authors: "Yash Akhauri, Ahmed F AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander M Rush, Safeen Huda, Mohamed S Abdelfattah" + pdf: "https://arxiv.org/abs/2406.16635" + conference: EMNLP 2024 + - title: "Simple and Effective Masked Diffusion Language Models" + authors: "Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T Chiu, Alexander Rush, Volodymyr Kuleshov" + pdf: "https://arxiv.org/abs/2406.07524" + conference: NeurIPS 2024 + - title: "Entity disambiguation via fusion entity decoding" + authors: "Junxiong Wang, Ali Mousavi, Omar Attia, Ronak Pradeep, Saloni Potdar, Alexander M Rush, Umar Farooq Minhas, Yunyao Li" + pdf: "https://arxiv.org/abs/2404.01626" + conference: NAACL 2024 + - title: "MambaByte: Token-free Selective State Space Model" + authors: "Junxiong Wang, Tushaar Gangavarapu, Jing Nathan Yan, Alexander M. Rush" + pdf: https://arxiv.org/abs/2401.13660 + conference: COLM 2024 + - title: "Zephyr: Direct Distillation of LM Alignment" + authors: "Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, Thomas Wolf" + pdf: "https://arxiv.org/pdf/2310.16944.pdf" + conference: COLM 2024 + image: + - title: "Guess and Sketch: Language Model Guided Transpilation" + authors: "Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander M. Rush" + pdf: "https://arxiv.org/pdf/2309.14396.pdf" + conference: ICLR 2024 + image: + - title: "Symbolic Planning and Code Generation for Grounded Dialogue" + authors: "Justin T. Chiu, Wenting Zhao, Derek Chen, Saujas Vaduguru, Alexander M. Rush, Daniel Fried" + pdf: "https://arxiv.org/pdf/2310.17140.pdf" + conference: EMNLP 2023 + image: + - title: "Teal: Learning-Accelerated Optimization of WAN Traffic Engineering" + authors: "Zhiying Xu, Francis Y. Yan, Rachee Singh, Justin T. Chiu, Alexander M. Rush, Minlan Yu" + pdf: "https://arxiv.org/abs/2210.13763" + conference: "SIGCOMM 2023" + image: + - title: "Text Embeddings Reveal (Almost) As Much As Text" + authors: "John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov, Alexander M. Rush" + pdf: "https://arxiv.org/pdf/2310.06816.pdf" + conference: EMNLP 2023 + image: + - title: "Tree Prompting: Efficient Task Adaptation without Fine-Tuning" + authors: "John X. Morris, Chandan Singh, Alexander M. Rush, Jianfeng Gao, Yuntian Deng" + pdf: "https://arxiv.org/pdf/2310.14034.pdf" + conference: EMNLP 2023 + image: + - title: "HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervision" + authors: "Wenting Zhao, Justin T. Chiu, Claire Cardie, Alexander M. Rush" + pdf: "https://arxiv.org/pdf/2305.14237.pdf" + conference: EMNLP 2023 + image: + - title: "Pretraining Without Attention" + authors: "Junxiong Wang, Jing Nathan Yan, Albert Gu, Alexander M. Rush" + pdf: "https://arxiv.org/pdf/2212.10544.pdf" + conference: EMNLP 2023 Findings + image: /images/bigs.png + - title: "Scaling Data-Constrained Language Models" + authors: "Niklas Muennighoff, Alexander M. Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, Colin Raffel" + pdf: "https://arxiv.org/pdf/2305.16264.pdf" + conference: NeurIPS 2023 (Oral) + image: + - title: "OBELISC: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents" + authors: "Hugo Laurençon, Lucile Saulnier, Léo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov, Thomas Wang, Siddharth Karamcheti, Alexander M. Rush, Douwe Kiela, Matthieu Cord, Victor Sanh" + pdf: "https://arxiv.org/pdf/2306.16527.pdf" + conference: NeurIPS 2023 Dataset + image: "" + - title: "Abductive Commonsense Reasoning Exploiting Mutually Exclusive Explanations" + authors: "Wenting Zhao, Justin T. Chiu, Claire Cardie, Alexander M. Rush" + pdf: "https://arxiv.org/pdf/2305.14618.pdf" + conference: "ACL 2023" + image: "" + - title: "Markup-to-Image Diffusion Models with Scheduled Sampling" + authors: "Yuntian Deng, Noriyuki Kojima, Alexander M. Rush" + pdf: "https://arxiv.org/abs/2210.05147" + conference: "ICLR 2023" + image: "" + - title: "A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management" + authors: "Thierry Tambe, Jeff Zhang, Coleman Hooper, Tianyu Jia, Paul N. Whatmough, Joseph Zuckerman, Maico Cassel dos Santos, Erik Jens Loscalzo, Davide Giri, Kenneth L. Shepard, Luca P. Carloni, Alexander M. Rush, David Brooks, Gu-Yeon Wei" + pdf: + conference: "ISSCC 2023" + image: "" + - title: "BLOOM: A 176B-Parameter Open-Access Multilingual Language Model" + authors: BigScience Workshop + pdf: https://arxiv.org/abs/2211.05100 + conference: Arxiv Preprint + - title: "Named Tensor Notation" + authors: David Chiang, Alexander M. Rush, Boaz Barak + pdf: https://arxiv.org/pdf/2102.13196.pdf + image: /images/ntn.png + conference: TMLR 2022 + - title: "Xatu: boosting existing DDoS detection systems using auxiliary signals" + authors: Zhiying Xu, Sivaramakrishnan Ramanathan, Alexander Rush, Jelena Mirkovic, Minlan Yu + pdf: https://dl.acm.org/doi/abs/10.1145/3555050.3569121 + image: /images/xatu.png + conference: CoNEXT 2022 + - title: "Unsupervised Text Deidentification" + authors: John X Morris, Justin T Chiu, Ramin Zabih, Alexander M Rush + pdf: https://arxiv.org/pdf/2210.11528.pdf + image: /images/deid.png + conference: EMNLP Findings 2022 + - title: "Model Criticism for Long-Form Text Generation" + authors: Yuntian Deng, Volodymyr Kuleshov, Alexander M Rush + pdf: https://arxiv.org/pdf/2210.08444.pdf + image: /images/modcrit.png + conference: EMNLP 2022 + - title: "Evaluate and Evaluation on the Hub: Better Best Practices for Data and Model Measurement" + authors: Leandro von Werra et al. + pdf: https://arxiv.org/abs/2210.01970 + image: /images/evalhub.png + conference: EMNLP Demos 2022 (Best Demo) + - title: "Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models" + authors: Hendik Strobelt et al. + pdf: https://ieeexplore.ieee.org/abstract/document/9908590 + image: + conference: IEEE Trans on Visualization 2022 + - title: "A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs" + authors: Thierry Tambe et al. + pdf: https://discovery.ucl.ac.uk/id/eprint/10150658/1/A_16-nm_SoC_for_Noise-Robust_Speech.pdf + image: /images/soundsource.png + conference: IEEE Solid-State Circuits 2022 + - title: "Promptsource: An integrated development environment and repository for natural language prompts" + authors: Stephen Bach et al. + pdf: https://arxiv.org/abs/2202.01279 + image: "https://github.com/bigscience-workshop/promptsource/raw/main/assets/promptsource_app.png" + conference: ACL Demo 2022 + - title: "End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman" + authors: Samantha Petti, et al. + pdf: http://repository.cshl.edu/id/eprint/40409/1/2021.Petti.multiple_sequence_alignments.pdf + image: "https://pbs.twimg.com/media/FCfRXOJXEAITHZ0?format=jpg&name=large" + conference: Bioinformatics + - title: "Multitask prompted training enables zero-shot task generalization" + authors: Victor Sanh, et al. + pdf: https://arxiv.org/pdf/2110.08207 + image: "https://github.com/bigscience-workshop/promptsource/raw/main/assets/promptsource_app.png" + conference: ICLR 2022 + - title: "Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field" + authors: Stanislav Lukyanenko et al. + pdf: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526069/ + image: + conference: MICCAI 2021 + - title: "Rationales for sequential predictions" + authors: Keyon Vafa, Yuntian Deng, David Blei, Alexander Rush + pdf: https://arxiv.org/pdf/2109.06387 + image: /images/seqrat.png + conference: EMNLP 2021 + - title: "Low-Rank Constraints for Fast Inference in Structured Models" + authors: Justin Chiu, Yuntian Deng, and Alexander M. Rush + pdf: "https://proceedings.neurips.cc/paper/2021/file/16c0d78ef6a76b5c247113a4c9514059-Paper.pdf" + image: + conference: NeurIPS 2021 + - title: "Conference demographics and footprint changed by virtual platforms" + authors: Matthe Skiles et al. + pdf: https://www.nature.com/articles/s41893-021-00823-2 + image: https://media.springernature.com/full/springer-static/image/art%3A10.1038%2Fs41893-021-00823-2/MediaObjects/41893_2021_823_Fig1_HTML.png?as=webp + conference: Nature Sustainability + - title: "Sequence-to-Lattice Models for Fast Translation" + authors: Yuntian Deng and Alexander M. Rush + pdf: https://aclanthology.org/2021.findings-emnlp.318.pdf + image: "https://github.com/harvardnlp/cascaded-generation/raw/master/cascaded-generation-fastest.gif" + conference: EMNLP Findings Short 2021 + - title: "Datasets: A Community Library for Natural Language Processing" + authors: Quentin Lhoest et al + pdf: https://arxiv.org/pdf/2109.02846.pdf + image: "https://huggingface.co/docs/datasets/_images/datasets_logo.png" + conference: EMNLP Demos 2021 (Best Demo) + - title: "EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference" + authors: Thierry Tambe and Others + pdf: https://arxiv.org/pdf/2011.14203.pdf + image: /images/edgebert.png + conference: IEEE MICRO 2021 + - title: "GenNI: Human-AI Collaboration for Data-Backed Text Generation" + authors: Hendrik Strobelt, Jambay Kinley, Robert Krueger, Johanna Beyer, Alexander M. Rush, Hanspeter Pfister + pdf: + image: /images/genni.png + conference: IEEE VIS 2021 + - title: "Parameter-efficient transfer learning with diff pruning" + authors: Demi Guo, Alexander M. Rush, Yoon Kim + pdf: https://arxiv.org/pdf/2012.07463.pdf + image: /images/diffprune.png + conference: ACL 2021 + - title: "How many data points is a prompt worth?" + authors: Teven Le Scao, Alexander M. Rush + pdf: https://aclanthology.org/2021.naacl-main.208.pdf + image: /images/prompt.png + conference: NAACL Short 2021 (Best Paper - Runner-Up) + - title: "Block pruning for faster transformers" + authors: François Lagunas, Ella Charlaix, Victor Sanh, Alexander M Rush + pdf: https://arxiv.org/pdf/2109.04838 + image: + conference: ACL 2021 + - title: "Low-Complexity Probing via Finding Subnetworks" + authors: Steven Cao, Victor Sanh, Alexander M. Rush + pdf: https://aclanthology.org/2021.naacl-main.74/ + image: /images/probing.png + conference: NAACL Short 2021 + - title: "Template Filling with Generative Transformers" + authors: Xinya Du, Alexander M. Rush, Claire Cardie + pdf: https://aclanthology.org/2021.naacl-main.70/ + image: + conference: NAACL Short 2021 + - title: "9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET" + authors: Thierry Tambe, En-Yu Yang, Glenn G Ko, Yuji Chai, Coleman Hooper, Marco Donato, Paul N Whatmough, Alexander M Rush, David Brooks, Gu-Yeon Wei + pdf: https://ieeexplore.ieee.org/abstract/document/9366062 + image: + conference: IEEE International Solid-State Circuits Conference 2021 + - title: "Cascaded Text Generation with Markov Transformers" + authors: Yuntian Deng, Alexander M. Rush + pdf: https://arxiv.org/pdf/2006.01112 + image: /images/cascade.png + conference: NeurIPS 2020 + - title: "Latent Template Induction with Gumbel-CRFs" + authors: Yao Fu, Chuanqi Tan, Bin Bi, Mosha Chen, Yansong Feng, Alexander Rush + pdf: https://github.com/FranxYao/Gumbel-CRF + image: https://raw.githubusercontent.com/FranxYao/Gumbel-CRF/main/img/model_github.png + conference: NeurIPS 2020 + - title: "Movement Pruning: Adaptive Sparsity by Fine-Tuning" + authors: Victor Sanh, Thomas Wolf, Alexander M. Rush + pdf: https://arxiv.org/pdf/2005.07683 + image: /images/movement.png + conference: NeurIPS 2020 + - title: "Scaling Hidden Markov Language Models" + authors: Justin T. Chiu, Alexander M. Rush + pdf: https://arxiv.org/abs/2011.04640 + image: /images/hmm.png + conference: EMNLP 2020 + - title: "Adversarial Semantic Collisions" + authors: Congzheng Song, Alexander M. Rush, Vitaly Shmatikov + pdf: https://www.cs.cornell.edu/~shmat/shmat_emnlp20.pdf + image: /images/shmat_emnlp20.png + conference: EMNLP 2020 + - title: "Sequence-Level Mixed Sample Data Augmentation" + authors: Demi Guo, Yoon Kim, Alexander M. Rush + pdf: https://www.aclweb.org/anthology/2020.emnlp-main.447/ + image: + conference: EMNLP 2020 + - title: "AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference" + authors: Thierry Tambe, En-Yu Yang, Zishen Wan, Yuntian Deng, Vijay Janapa Reddi, Alexander Rush, David Brooks, Gu-Yeon Wei + pdf: https://arxiv.org/pdf/1909.13271 + image: /images/adapt.png + conference: DAC 2020 (Best Paper) + - title: "Transformers: State-of-the-art Natural Language Processing" + authors: Thomas Wolf et al + pdf: https://arxiv.org/pdf/1910.03771 + image: /images/transformers.png + conference: EMNLP Demos 2020 (Best Demo) + - title: "Torch-Struct: Deep Structured Prediction Library" + authors: Alexander Rush + pdf: https://arxiv.org/pdf/2002.00876 + image: https://github.com/harvardnlp/pytorch-struct/raw/master/download.png + conference: ACL Demos 2020 (Best Demo Honorable Mention) + - title: "What is Learned in Visually Grounded Neural Syntax Acquisition" + authors: Noriyuki Kojima, Hadar Averbuch-Elor, Alexander M. Rush, Yoav Artzi + pdf: https://arxiv.org/pdf/2005.01678 + image: /images/learned.png + conference: ACL 2020 (Short) + - title: "Posterior Control of Blackbox Generation" + authors: Xiang Lisa Li, Alexander M. Rush + pdf: https://arxiv.org/pdf/2005.04560 + image: /images/posterior.png + conference: ACL 2020 + - title: "Automating Botnet Detection with Graph Neural Networks" + authors: Jiawei Zhou, Zhiying Xu, Alexander M. Rush, Minlan Yu + pdf: https://arxiv.org/pdf/2003.06344 + image: /images/botnet.png + conference: AutoML for Networking and Systems Workshop + - title: "LAN -- A materials notation for 2D layered assemblies" + authors: Georgios A. Tritsaris, Yiqi Xie, Alexander M. Rush, Stephen Carr, Marios Mattheakis, Efthimios Kaxiras + pdf: https://arxiv.org/pdf/1910.03413 + image: /images/lan.png + conference: + - title: "MASR: A Modular Accelerator for Sparse RNNs" + authors: Udit Gupta, Brandon Reagen, Lillian Pentecost, Marco Donato, Thierry Tambe, Alexander M. Rush, Gu-Yeon Wei, David Brooks + pdf: + image: /images/MASR.png + conference: PACT 2019 + - title: "Commonsense Knowledge Mining from Pretrained Models" + authors: "Joe Davison, Joshua Feldman and Alexander Rush" + pdf: + conference: EMNLP 2019 + - title: "Neural Linguistic Steganography" + authors: Zachary Ziegler, Yuntian Deng and Alexander Rush + pdf: https://arxiv.org/abs/1909.01496 + conference: EMNLP 2019 + - title: "Compound Probabilistic Context-Free Grammars for Grammar Induction" + authors: Yoon Kim, Chris Dyer, Alexander M. Rush + pdf: https://www.aclweb.org/anthology/P19-1228/ + code: https://github.com/harvardnlp/compound-pcfg + image: /images/Tree.png + conference: ACL 2019 - - title: "Visual Interaction with Deep Learning Models through Collaborative Semantic Inference" - authors: Gehrmann S, Strobelt H, Krueger R, Pfister H, and Alexander M. Rush - pdf: https://arxiv.org/abs/1907.10739 - code: https://vcg.seas.harvard.edu/publications/visual-interaction-with-deep-learning-models-through-collaborative-semantic-inference - image: https://vcg.seas.harvard.edu/content/3-publications/20191020-visual-interaction-with-deep-learning-models-through-collaborative-semantic-inference/csiteaser.png - conference: InfoVis 2019 + - title: "Visual Interaction with Deep Learning Models through Collaborative Semantic Inference" + authors: Gehrmann S, Strobelt H, Krueger R, Pfister H, and Alexander M. Rush + pdf: https://arxiv.org/abs/1907.10739 + code: https://vcg.seas.harvard.edu/publications/visual-interaction-with-deep-learning-models-through-collaborative-semantic-inference + image: https://vcg.seas.harvard.edu/content/3-publications/20191020-visual-interaction-with-deep-learning-models-through-collaborative-semantic-inference/csiteaser.png + conference: InfoVis 2019 - - title: "Simple Unsupervised Summarization by Contextual Matching" - authors: Jiawei Zhou, Alexander M. Rush - pdf: https://www.aclweb.org/anthology/P19-1503 - image: /images/Tree.png - conference: ACL 2019 - - title: "GLTR: Statistical Detection and Visualization of Generated Text" - authors: Sebastian Gehrmann, Hendrik Strobelt, Alexander M Rush - pdf: https://arxiv.org/abs/1906.04043 - code: http://gltr.io/dist/index.html - image: http://rush-nlp.com/images/gltr.png - conference: ACL Demo 2019 (Best Demo Honorable Mention) + - title: "Simple Unsupervised Summarization by Contextual Matching" + authors: Jiawei Zhou, Alexander M. Rush + pdf: https://www.aclweb.org/anthology/P19-1503 + image: /images/Tree.png + conference: ACL 2019 + - title: "GLTR: Statistical Detection and Visualization of Generated Text" + authors: Sebastian Gehrmann, Hendrik Strobelt, Alexander M Rush + pdf: https://arxiv.org/abs/1906.04043 + code: http://gltr.io/dist/index.html + image: http://rush-nlp.com/images/gltr.png + conference: ACL Demo 2019 (Best Demo Honorable Mention) - - title: "Unsupervised Recurrent Neural Network Grammars" - authors: Yoon Kim, Alexander M. Rush, Lei Yu, Adhiguna Kuncoro, Chris Dyer, Gabor Melis - pdf: https://arxiv.org/pdf/1904.03746.pdf - code: https://github.com/harvardnlp/urnng - image: /images/urnng.png - conference: NAACL 2019 + - title: "Unsupervised Recurrent Neural Network Grammars" + authors: Yoon Kim, Alexander M. Rush, Lei Yu, Adhiguna Kuncoro, Chris Dyer, Gabor Melis + pdf: https://arxiv.org/pdf/1904.03746.pdf + code: https://github.com/harvardnlp/urnng + image: /images/urnng.png + conference: NAACL 2019 - - title: "Avoiding Latent Variable Collapse With Generative Skip Models" - authors: Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei - conference: AISTATS 2019 - pdf: https://arxiv.org/pdf/1807.04863.pdf - image: /images/skipvae.png + - title: "Avoiding Latent Variable Collapse With Generative Skip Models" + authors: Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei + conference: AISTATS 2019 + pdf: https://arxiv.org/pdf/1807.04863.pdf + image: /images/skipvae.png - - title: "Tensor Variable Elimination for Plated Factor Graphs" - authors: Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin Chiu, Neeraj Pradhan, Alexander Rush, Noah Goodman - conference: ICML 2019 - pdf: https://arxiv.org/pdf/1902.03210.pdf - code: https://github.com/justinchiu/sentclass - image: /images/tensorelimination.png - - title: "Latent Normalizing Flows for Discrete Sequences" - authors: Zachary M. Ziegler, Alexander M. Rush - conference: ICML 2019 - pdf: https://arxiv.org/pdf/1901.10548 - code: https://github.com/harvardnlp/TextFlow - image: /images/textflow.png - - title: "Deep Latent-Variable Models for Natural Language" - authors: Yoon Kim, Sam Wiseman, Alexander M. Rush - conference: EMNLP 2018 (Tutorial) - pdf: https://github.com/harvardnlp/DeepLatentNLP/raw/master/tutorial_deep_latent.pdf - code: http://nlp.seas.harvard.edu/latent-nlp-tutorial.html - image: http://nlp.seas.harvard.edu/images/vae.png + - title: "Tensor Variable Elimination for Plated Factor Graphs" + authors: Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin Chiu, Neeraj Pradhan, Alexander Rush, Noah Goodman + conference: ICML 2019 + pdf: https://arxiv.org/pdf/1902.03210.pdf + code: https://github.com/justinchiu/sentclass + image: /images/tensorelimination.png + - title: "Latent Normalizing Flows for Discrete Sequences" + authors: Zachary M. Ziegler, Alexander M. Rush + conference: ICML 2019 + pdf: https://arxiv.org/pdf/1901.10548 + code: https://github.com/harvardnlp/TextFlow + image: /images/textflow.png + - title: "Deep Latent-Variable Models for Natural Language" + authors: Yoon Kim, Sam Wiseman, Alexander M. Rush + conference: EMNLP 2018 (Tutorial) + pdf: https://github.com/harvardnlp/DeepLatentNLP/raw/master/tutorial_deep_latent.pdf + code: http://nlp.seas.harvard.edu/latent-nlp-tutorial.html + image: http://nlp.seas.harvard.edu/images/vae.png - - title: "End-to-End Content and Plan Selection for Data-to-Text Generation" - authors: Sebastian Gehrmann, Falcon Z. Dai, Henry Elder, Alexander M. Rush - conference: INLG 2018 - pdf: https://arxiv.org/pdf/1810.04700 - code: https://github.com/sebastianGehrmann/diverse_ensembling - image: /images/diverse_ensembling.png + - title: "End-to-End Content and Plan Selection for Data-to-Text Generation" + authors: Sebastian Gehrmann, Falcon Z. Dai, Henry Elder, Alexander M. Rush + conference: INLG 2018 + pdf: https://arxiv.org/pdf/1810.04700 + code: https://github.com/sebastianGehrmann/diverse_ensembling + image: /images/diverse_ensembling.png - - title: "Latent Alignment and Variational Attention" - authors: Yuntian Deng*, Yoon Kim*, Justin Chiu, Demi Guo, Alexander M. Rush - conference: NIPS 2018 - pdf : https://arxiv.org/pdf/1807.03756.pdf - code: https://github.com/harvardnlp/var-attn - image: /images/VariationalAttention.png - - title: "Learning Neural Templates for Text Generation" - authors: Sam Wiseman, Stuart M. Shieber, Alexander Rush - conference: EMNLP 2018 - code: https://github.com/harvardnlp/neural-template-gen - pdf : https://arxiv.org/abs/1808.10122 - image: /images/template.png + - title: "Latent Alignment and Variational Attention" + authors: Yuntian Deng*, Yoon Kim*, Justin Chiu, Demi Guo, Alexander M. Rush + conference: NIPS 2018 + pdf: https://arxiv.org/pdf/1807.03756.pdf + code: https://github.com/harvardnlp/var-attn + image: /images/VariationalAttention.png + - title: "Learning Neural Templates for Text Generation" + authors: Sam Wiseman, Stuart M. Shieber, Alexander Rush + conference: EMNLP 2018 + code: https://github.com/harvardnlp/neural-template-gen + pdf: https://arxiv.org/abs/1808.10122 + image: /images/template.png - - title: "Bottom-Up Abstractive Summarization" - authors: Sebastian Gehrmann, Yuntian Deng, Alexander Rush - conference: EMNLP 2018 - pdf : https://arxiv.org/abs/1808.10792 - image: /images/bottomup.png + - title: "Bottom-Up Abstractive Summarization" + authors: Sebastian Gehrmann, Yuntian Deng, Alexander Rush + conference: EMNLP 2018 + pdf: https://arxiv.org/abs/1808.10792 + image: /images/bottomup.png - - title: "Training for Diversity in Image Paragraph Captioning" - authors: Luke Melas-Kyriazi, George Han, Alexander Rush - conference: EMNLP 2018 (Short) - pdf: https://www.aclweb.org/anthology/D18-1084 - image: /images/paracap.png - - title: "Entity Tracking Improves Cloze-style Reading Comprehension" - authors: Luong Hoang, Sam Wiseman, Alexander Rush - conference: EMNLP 2018 (Short) - pdf: https://www.aclweb.org/anthology/D18-1130 - image: /images/lambada.png + - title: "Training for Diversity in Image Paragraph Captioning" + authors: Luke Melas-Kyriazi, George Han, Alexander Rush + conference: EMNLP 2018 (Short) + pdf: https://www.aclweb.org/anthology/D18-1084 + image: /images/paracap.png + - title: "Entity Tracking Improves Cloze-style Reading Comprehension" + authors: Luong Hoang, Sam Wiseman, Alexander Rush + conference: EMNLP 2018 (Short) + pdf: https://www.aclweb.org/anthology/D18-1130 + image: /images/lambada.png - - title: "Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models " - authors: Hendrik Strobelt, Sebastian Gehrmann, Michael Behrisch, Adam Perer, Hanspeter Pfister, Alexander M. Rush - conference: VAST 2018, EMNLP-BlackBox 2018 (Best Paper - Honorable Mention) - pdf : https://arxiv.org/abs/1804.09299 - code : https://github.com/HendrikStrobelt/Seq2Seq-Vis - image: /images/s2s_dates_01.png - - title: "The Annotated Transformer" - authors: Alexander M. Rush - conference: ACL NLP-OSS 2018 - pdf : http://aclweb.org/anthology/W18-2509 - code: https://github.com/harvardnlp/annotated-transformer/blob/master/The%20Annotated%20Transformer.ipynb - image: /images/the-annotated-transformer_14_0.png - - title: "OpenNMT System Description for WNMT 2018: 800 words/sec on a single-core CPU" - authors: Jean Senellart, Dakun Zhang, Bo Wang, Guillaume Klein, J.P. Ramatchandirin, Josep Crego, Alexander M. Rush - conference: WNMT 2018 (First-Place CPU Speed/Memory) - pdf : http://aclweb.org/anthology/W18-2715 - image: /images/WNMT18_OpenNMT.png - - title: "Semi-Amortized Variational Autoencoders" - authors: Yoon Kim, Sam Wiseman, Andrew C. Miller, David Sontag, Alexander M. Rush - conference: ICML 2018 - pdf : https://arxiv.org/abs/1802.02550 - code : https://github.com/harvardnlp/sa-vae - image: /images/savae.png - - title: "Compressing Deep Neural Networks with Probabilistic Data Structures" - authors: Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks - conference: ICML 2018, SysML 2018 - pdf : https://www.sysml.cc/doc/68.pdf - image: /images/bloomier.png - - title: "Adapting Sequence Models for Sentence Correction" - authors: Allen Schmaltz, Yoon Kim, Alexander M. Rush, Stuart M. Shieber - conference: EMNLP 2017 - pdf : https://arxiv.org/abs/1707.09067 - image: /images/aesw2016.png - slides: - - title: "Challenges in Data-to-Document Generation" - authors: Sam Wiseman, Stuart M Shieber Alexander M. Rush - conference: EMNLP 2017 - pdf : https://arxiv.org/abs/1707.08052 - code : http://lstm.seas.harvard.edu/docgen - image: /images/docgen.png - slides: /slides/nmt17.pdf - - title: "Adversarially Regularized Autoencoders" - authors: Junbo Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, Yann LeCun - conference: ICML 2018, NIPS 2017 Workshop - pdf : https://arxiv.org/abs/1706.04223 - code : https://github.com/jakezhaojb/ARAE - image: /images/arae.png - - title: "OpenNMT: Open-Source Toolkit for Neural Machine Translation" - authors: Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush - conference: ACL Demo 2017 (Best Demo Runner-up) - pdf : https://arxiv.org/abs/1701.02810 - image: /images/overview.png - slides: - - title: "Dilated Convolutions for Modeling Long-Distance Genomic Dependencies" - authors: Ankit Gupta, Alexander M. Rush - conference: ICML CompBio 2017 (Best Poster) - pdf : https://arxiv.org/abs/1710.01278 - image: /images/ankit.png + - title: "Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models " + authors: Hendrik Strobelt, Sebastian Gehrmann, Michael Behrisch, Adam Perer, Hanspeter Pfister, Alexander M. Rush + conference: VAST 2018, EMNLP-BlackBox 2018 (Best Paper - Honorable Mention) + pdf: https://arxiv.org/abs/1804.09299 + code: https://github.com/HendrikStrobelt/Seq2Seq-Vis + image: /images/s2s_dates_01.png + - title: "The Annotated Transformer" + authors: Alexander M. Rush + conference: ACL NLP-OSS 2018 + pdf: http://aclweb.org/anthology/W18-2509 + code: https://github.com/harvardnlp/annotated-transformer/blob/master/The%20Annotated%20Transformer.ipynb + image: /images/the-annotated-transformer_14_0.png + - title: "OpenNMT System Description for WNMT 2018: 800 words/sec on a single-core CPU" + authors: Jean Senellart, Dakun Zhang, Bo Wang, Guillaume Klein, J.P. Ramatchandirin, Josep Crego, Alexander M. Rush + conference: WNMT 2018 (First-Place CPU Speed/Memory) + pdf: http://aclweb.org/anthology/W18-2715 + image: /images/WNMT18_OpenNMT.png + - title: "Semi-Amortized Variational Autoencoders" + authors: Yoon Kim, Sam Wiseman, Andrew C. Miller, David Sontag, Alexander M. Rush + conference: ICML 2018 + pdf: https://arxiv.org/abs/1802.02550 + code: https://github.com/harvardnlp/sa-vae + image: /images/savae.png + - title: "Compressing Deep Neural Networks with Probabilistic Data Structures" + authors: Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks + conference: ICML 2018, SysML 2018 + pdf: https://www.sysml.cc/doc/68.pdf + image: /images/bloomier.png + - title: "Adapting Sequence Models for Sentence Correction" + authors: Allen Schmaltz, Yoon Kim, Alexander M. Rush, Stuart M. Shieber + conference: EMNLP 2017 + pdf: https://arxiv.org/abs/1707.09067 + image: /images/aesw2016.png + slides: + - title: "Challenges in Data-to-Document Generation" + authors: Sam Wiseman, Stuart M Shieber Alexander M. Rush + conference: EMNLP 2017 + pdf: https://arxiv.org/abs/1707.08052 + code: http://lstm.seas.harvard.edu/docgen + image: /images/docgen.png + slides: /slides/nmt17.pdf + - title: "Adversarially Regularized Autoencoders" + authors: Junbo Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, Yann LeCun + conference: ICML 2018, NIPS 2017 Workshop + pdf: https://arxiv.org/abs/1706.04223 + code: https://github.com/jakezhaojb/ARAE + image: /images/arae.png + - title: "OpenNMT: Open-Source Toolkit for Neural Machine Translation" + authors: Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush + conference: ACL Demo 2017 (Best Demo Runner-up) + pdf: https://arxiv.org/abs/1701.02810 + image: /images/overview.png + slides: + - title: "Dilated Convolutions for Modeling Long-Distance Genomic Dependencies" + authors: Ankit Gupta, Alexander M. Rush + conference: ICML CompBio 2017 (Best Poster) + pdf: https://arxiv.org/abs/1710.01278 + image: /images/ankit.png - - title: "Image-to-Markup Generation with Coarse-to-Fine Attention" - authors: Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, and Alexander M. Rush - conference: ICML 2017 - pdf : http://lstm.seas.harvard.edu/latex/ - code : http://lstm.seas.harvard.edu/latex/ - image: https://camo.githubusercontent.com/5a6350632dd43b69fff7f41928f27b8c8eb9a7d9/687474703a2f2f6c73746d2e736561732e686172766172642e6564752f6c617465782f6d61746865782e706e67 - slides: /slides/icml17.pdf + - title: "Image-to-Markup Generation with Coarse-to-Fine Attention" + authors: Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, and Alexander M. Rush + conference: ICML 2017 + pdf: http://lstm.seas.harvard.edu/latex/ + code: http://lstm.seas.harvard.edu/latex/ + image: https://camo.githubusercontent.com/5a6350632dd43b69fff7f41928f27b8c8eb9a7d9/687474703a2f2f6c73746d2e736561732e686172766172642e6564752f6c617465782f6d61746865782e706e67 + slides: /slides/icml17.pdf - - title: "LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks" - authors: Hendrik Strobelt, Sebastian Gehrmann, Hanspeter Pfister, and Alexander M. Rush - conference: InfoVis 2017 - pdf : http://lstm.seas.harvard.edu/ - code : http://lstm.seas.harvard.edu/ - image: /images/small_teaser.png + - title: "LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks" + authors: Hendrik Strobelt, Sebastian Gehrmann, Hanspeter Pfister, and Alexander M. Rush + conference: InfoVis 2017 + pdf: http://lstm.seas.harvard.edu/ + code: http://lstm.seas.harvard.edu/ + image: /images/small_teaser.png - - title: "Structured Attention Networks" - authors: Yoon Kim, Carl Denton, Luong Hoang, and Alexander M. Rush - conference: ICLR 2017 - pdf : https://arxiv.org/abs/1702.00887 - code : http://github.com/harvardnlp/struct-attn - image: /images/struct.jpg - slides: /slides/iclr17.pdf + - title: "Structured Attention Networks" + authors: Yoon Kim, Carl Denton, Luong Hoang, and Alexander M. Rush + conference: ICLR 2017 + pdf: https://arxiv.org/abs/1702.00887 + code: http://github.com/harvardnlp/struct-attn + image: /images/struct.jpg + slides: /slides/iclr17.pdf - - title: "Lie-Access Neural Turing Machines" - authors: Greg Yang and Alexander M. Rush - conference: ICLR 2017 - pdf : http://lstm.seas.harvard.edu/lantm/ - code : http://lstm.seas.harvard.edu/lantm/ - image: /images/lantm.png - slides: + - title: "Lie-Access Neural Turing Machines" + authors: Greg Yang and Alexander M. Rush + conference: ICLR 2017 + pdf: http://lstm.seas.harvard.edu/lantm/ + code: http://lstm.seas.harvard.edu/lantm/ + image: /images/lantm.png + slides: - - title: Sequence-Level Knowledge Distillation - authors: Yoon Kim and Alexander M. Rush - conference: EMNLP 2016 - pdf : http://arxiv.org/pdf/1606.07947v1.pdf - image: /images/segknow.png - slides : /slides/emnlp16_seqkd.pdf - code: https://github.com/harvardnlp/seq2seq-attn + - title: Sequence-Level Knowledge Distillation + authors: Yoon Kim and Alexander M. Rush + conference: EMNLP 2016 + pdf: http://arxiv.org/pdf/1606.07947v1.pdf + image: /images/segknow.png + slides: /slides/emnlp16_seqkd.pdf + code: https://github.com/harvardnlp/seq2seq-attn - - title: Sequence-to-Sequence Learning as Beam-Search Optimization - authors: Sam Wiseman and Alexander M. Rush - conference: EMNLP 2016 (Best Paper Runner-Up) - pdf : http://arxiv.org/pdf/1606.02960.pdf - image: /images/seqseq.png - slides : /slides/emnlp16_bso.pdf + - title: Sequence-to-Sequence Learning as Beam-Search Optimization + authors: Sam Wiseman and Alexander M. Rush + conference: EMNLP 2016 (Best Paper Runner-Up) + pdf: http://arxiv.org/pdf/1606.02960.pdf + image: /images/seqseq.png + slides: /slides/emnlp16_bso.pdf - - title: An Embedding Model for Predicting Roll-Call Votes - authors: Peter Kraft, Hirsh Jain, and Alexander M. Rush - conference: Proceedings of EMNLP 2016 - image: /images/poliemb.png - pdf: https://www.aclweb.org/anthology/D/D16/D16-1221.pdf - slides : /slides/emnlp16_poli.pdf + - title: An Embedding Model for Predicting Roll-Call Votes + authors: Peter Kraft, Hirsh Jain, and Alexander M. Rush + conference: Proceedings of EMNLP 2016 + image: /images/poliemb.png + pdf: https://www.aclweb.org/anthology/D/D16/D16-1221.pdf + slides: /slides/emnlp16_poli.pdf - - title: Word Ordering Without Syntax - authors: Allen Schmaltz, Alexander M. Rush, and Stuart M. Shieber - conference: EMNLP 2016 - pdf : https://arxiv.org/abs/1604.08633 - image: /images/wordorder.png - slides : /slides/emnlp16_order.pdf - code: https://github.com/allenschmaltz/word_ordering/ + - title: Word Ordering Without Syntax + authors: Allen Schmaltz, Alexander M. Rush, and Stuart M. Shieber + conference: EMNLP 2016 + pdf: https://arxiv.org/abs/1604.08633 + image: /images/wordorder.png + slides: /slides/emnlp16_order.pdf + code: https://github.com/allenschmaltz/word_ordering/ - - title: Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction - authors: Allen Schmaltz, Yoon Kim, Alexander M. Rush, and Stuart M. Shieber - conference: Workshop Submission for AESW 2016 (Top Performing System) - pdf : /papers/aesw2016.pdf - image: /images/aesw2016.png - slides: /slides/naacl16_grammar.pdf + - title: Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction + authors: Allen Schmaltz, Yoon Kim, Alexander M. Rush, and Stuart M. Shieber + conference: Workshop Submission for AESW 2016 (Top Performing System) + pdf: /papers/aesw2016.pdf + image: /images/aesw2016.png + slides: /slides/naacl16_grammar.pdf - - title: Learning Global Features for Coreference Resolution - authors : Sam Wiseman, Alexander M. Rush, and Stuart M. Shieber - conference : NAACL 2016 - code : https://github.com/swiseman/nn_coref - pdf : /papers/corefmain.pdf - image : /images/cluster_viz.png + - title: Learning Global Features for Coreference Resolution + authors: Sam Wiseman, Alexander M. Rush, and Stuart M. Shieber + conference: NAACL 2016 + code: https://github.com/swiseman/nn_coref + pdf: /papers/corefmain.pdf + image: /images/cluster_viz.png - - title: Abstractive Sentence Summarization with Attentive Recurrent Neural Networks - authors : Sumit Chopra, Michael Auli, and Alexander M. Rush - conference : NAACL 2016 - code : https://github.com/facebook/NAMAS - pdf : /papers/naacl16_summary.pdf - image : /images/summary2.png + - title: Abstractive Sentence Summarization with Attentive Recurrent Neural Networks + authors: Sumit Chopra, Michael Auli, and Alexander M. Rush + conference: NAACL 2016 + code: https://github.com/facebook/NAMAS + pdf: /papers/naacl16_summary.pdf + image: /images/summary2.png - - title: Character-Aware Neural Language Models - authors : Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush - conference : AAAI 2016 - code : https://github.com/yoonkim/lstm-char-cnn - pdf : https://arxiv.org/pdf/1508.06615v4 - slides : /slides/aaai16.pdf - image : /images/charrnn.png + - title: Character-Aware Neural Language Models + authors: Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush + conference: AAAI 2016 + code: https://github.com/yoonkim/lstm-char-cnn + pdf: https://arxiv.org/pdf/1508.06615v4 + slides: /slides/aaai16.pdf + image: /images/charrnn.png - - title: A Neural Attention Model for Abstractive Sentence Summarization - authors : Alexander M. Rush, Sumit Chopra, and Jason Weston - conference : EMNLP 2015. - pdf : http://arxiv.org/pdf/1509.00685.pdf - code : https://github.com/facebook/NAMAS - slides : /slides/emnlp15.pdf - image : /images/summary.png + - title: A Neural Attention Model for Abstractive Sentence Summarization + authors: Alexander M. Rush, Sumit Chopra, and Jason Weston + conference: EMNLP 2015. + pdf: http://arxiv.org/pdf/1509.00685.pdf + code: https://github.com/facebook/NAMAS + slides: /slides/emnlp15.pdf + image: /images/summary.png - - title: Towards AI-Complete Question Answering A Set of Prerequisite Toy Tasks - authors: Jason Weston, Antoine Bordes, Sumit Chopra, Tomas Mikolov, and Alexander M. Rush - pdf : http://arxiv.org/pdf/1502.05698.pdf - conference: ArXiv Preprint - image : /images/babi.png + - title: Towards AI-Complete Question Answering A Set of Prerequisite Toy Tasks + authors: Jason Weston, Antoine Bordes, Sumit Chopra, Tomas Mikolov, and Alexander M. Rush + pdf: http://arxiv.org/pdf/1502.05698.pdf + conference: ArXiv Preprint + image: /images/babi.png - - title: Learning Anaphoricity and Antecedent Ranking Features for Coreference Resolution - authors : Sam Wiseman, Alexander M. Rush, Jason Weston, and Stuart M. Shieber - conference : ACL 2015. - pdf : http://people.seas.harvard.edu/~srush/acl15.pdf - code : https://github.com/swiseman/nn_coref - slides : /slides/acl15_pres.pdf - image : /images/acl15.png + - title: Learning Anaphoricity and Antecedent Ranking Features for Coreference Resolution + authors: Sam Wiseman, Alexander M. Rush, Jason Weston, and Stuart M. Shieber + conference: ACL 2015. + pdf: http://people.seas.harvard.edu/~srush/acl15.pdf + code: https://github.com/swiseman/nn_coref + slides: /slides/acl15_pres.pdf + image: /images/acl15.png - - title: A Fast Variational Approach for Learning Markov Random Field Language Models - authors: Yacine Jernite, Alexander M. Rush, and David Sontag - conference : ICML 2015. - code : https://github.com/srush/MRF-LM/ - slides : http://people.seas.harvard.edu/~srush/ICMLpresentationFinalNoAnimation.pdf - pdf : http://people.seas.harvard.edu/~srush/icml15.pdf - image : /images/icml15.png + - title: A Fast Variational Approach for Learning Markov Random Field Language Models + authors: Yacine Jernite, Alexander M. Rush, and David Sontag + conference: ICML 2015. + code: https://github.com/srush/MRF-LM/ + slides: http://people.seas.harvard.edu/~srush/ICMLpresentationFinalNoAnimation.pdf + pdf: http://people.seas.harvard.edu/~srush/icml15.pdf + image: /images/icml15.png - - title: Transforming Dependencies into Phrase Structures - authors: Lingpeng Kong, Alexander M. Rush, and Noah A. Smith - conference: NAACL 2015. - slides: http://people.seas.harvard.edu/~srush/naacl_poster.pdf - pdf: http://people.seas.harvard.edu/~srush/naacl15.pdf - code : https://github.com/ikekonglp/PAD - image : /images/naacl14.png + - title: Transforming Dependencies into Phrase Structures + authors: Lingpeng Kong, Alexander M. Rush, and Noah A. Smith + conference: NAACL 2015. + slides: http://people.seas.harvard.edu/~srush/naacl_poster.pdf + pdf: http://people.seas.harvard.edu/~srush/naacl15.pdf + code: https://github.com/ikekonglp/PAD + image: /images/naacl14.png diff --git a/_site/css/main.css b/_site/css/main.css index e7d57a2..99cc5b2 100644 --- a/_site/css/main.css +++ b/_site/css/main.css @@ -1,471 +1,259 @@ -/** - * Reset some basic elements - */ -body, h1, h2, h3, h4, h5, h6, -p, blockquote, pre, hr, -dl, dd, ol, ul, figure { - margin: 0; - padding: 0; } - -/** - * Basic styling - */ -body { - font: 400 16px/1.5 "Helvetica Neue", Helvetica, Arial, sans-serif; - color: #111; - background-color: #fdfdfd; - -webkit-text-size-adjust: 100%; - -webkit-font-feature-settings: "kern" 1; - -moz-font-feature-settings: "kern" 1; - -o-font-feature-settings: "kern" 1; - font-feature-settings: "kern" 1; - font-kerning: normal; } - -/** - * Set `margin-bottom` to maintain vertical rhythm - */ -h1, h2, h3, h4, h5, h6, -p, blockquote, 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%%%------------------------------------------------------------------------ \begin{minipage}[t]{2.95in} - \flushright {\footnotesize \href{http://rush-nlp.com}{Cornell University} \\ Cornell Tech, \\ \vspace{-0.05in} New York, NY } + \flushright {\footnotesize \href{http://rush-nlp.com}{Cornell University} \\ Cornell Tech, \\ \vspace{-0.05in} New York, NY } \end{minipage} \hfill @@ -159,10 +159,10 @@ %\end{minipage} \hfill \begin{minipage}[t]{1.7in} - \flushright %\footnotesize Phone: \myphone \\ - {\scriptsize \texttt{\href{mailto:\myemail}{\myemail}}} \\ - {\scriptsize \texttt{\href{\myweb}{\myweb}}} \\ - {\scriptsize \texttt{\href{http://twitter.com/\myfax}{@\myfax}}} \\ + \flushright %\footnotesize Phone: \myphone \\ + {\scriptsize \texttt{\href{mailto:\myemail}{\myemail}}} \\ + {\scriptsize \texttt{\href{\myweb}{\myweb}}} \\ + {\scriptsize \texttt{\href{http://twitter.com/\myfax}{@\myfax}}} \\ \end{minipage} @@ -210,36 +210,36 @@ \marginhead{ {\vskip 0.4em} Awards} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} -2023 & Best Paper Runner-up - NeurIPS \\ - & Outstanding Paper - EMNLP \\ -2021 & Best Demo Paper - EMNLP \\ - & Outstanding Short Paper - NAACL \\ - & Sloan Fellowship\\ -2020 & Best Demo Paper (Runner-Up), ACL \\ -& Best Paper - DAC (Hardware) \\ -& Best Demo Paper - EMNLP \\ -2019 & NSF Career Award \\ -& Best Demo Paper - Nominee, ACL \\ -2018 & Senior Program Chair, ICLR \\ -& Best Paper - Runner-Up, VAST (Visualization) \\ -2017 & Best Demo - Runner-Up, ACL \\ - & Invitation IJCAI Early Research Spotlight \\ -& Best Paper - Runner-Up, EMNLP \\ -2015 & NIPS Deep Learning Symposium (Invited Paper) \\ -2012 & Best Paper Award, NAACL \\ -2010 & Best Paper Award, EMNLP \\ + 2023 & Best Paper Runner-up - NeurIPS \\ + & Outstanding Paper - EMNLP \\ + 2021 & Best Demo Paper - EMNLP \\ + & Outstanding Short Paper - NAACL \\ + & Sloan Fellowship \\ + 2020 & Best Demo Paper (Runner-Up), ACL \\ + & Best Paper - DAC (Hardware) \\ + & Best Demo Paper - EMNLP \\ + 2019 & NSF Career Award \\ + & Best Demo Paper - Nominee, ACL \\ + 2018 & Senior Program Chair, ICLR \\ + & Best Paper - Runner-Up, VAST (Visualization) \\ + 2017 & Best Demo - Runner-Up, ACL \\ + & Invitation IJCAI Early Research Spotlight \\ + & Best Paper - Runner-Up, EMNLP \\ + 2015 & NIPS Deep Learning Symposium (Invited Paper) \\ + 2012 & Best Paper Award, NAACL \\ + 2010 & Best Paper Award, EMNLP \\ \end{tabular} \marginhead{ {\vskip 0.4em} Grants} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} -2019 & NSF Career Award \\ -& Sony Faculty Awards \\ -2018& Google, Facebook, and Amazon AWS Faculty Awards \\ -2017 & Bloomberg and Intel AI Collaboration Faculty Awards \\ -2016 & Microsoft Azure and Samsung AI Award \\ -2015 & Google Faculty Award \\ + 2019 & NSF Career Award \\ + & Sony Faculty Awards \\ + 2018 & Google, Facebook, and Amazon AWS Faculty Awards \\ + 2017 & Bloomberg and Intel AI Collaboration Faculty Awards \\ + 2016 & Microsoft Azure and Samsung AI Award \\ + 2015 & Google Faculty Award \\ \end{tabular} \pagebreak @@ -276,505 +276,542 @@ \noindent\textbf{All Conference Papers \vspace{0.01in}} -[1] \ind Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2309.14396.pdf }{ Guess and Sketch: Language Model Guided Transpilation.} }\emph{ Preprint } +[1] \ind J. O. Yin, Alexander Rush. \emph{\href{ https://arxiv.org/abs/2410.16208 }{ Compute-Constrained Data Selection.} }\emph{ Preprint 2024 } \medskip -[2] \ind Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, Thomas Wolf. \emph{\href{ https://arxiv.org/pdf/2310.16944.pdf }{ Zephyr: Direct Distillation of LM Alignment.} }\emph{ Preprint } +[2] \ind J. X. Morris, Alexander Rush. \emph{\href{ https://arxiv.org/abs/2410.02525 }{ Contextual Document Embeddings.} }\emph{ Preprint 2024 } \medskip -[3] \ind Justin T. Chiu, Wenting Zhao, Derek Chen, Saujas Vaduguru, Alexander M. Rush, Daniel Fried. \emph{\href{ https://arxiv.org/pdf/2310.17140.pdf }{ Symbolic Planning and Code Generation for Grounded Dialogue.} }\emph{ EMNLP 2023 } +[3] \ind Y. Lu, J. N. Yan, S. Yang, J. T. Chiu, S. Ren, F. Yuan, W. Zhao, Z. Wu, Alexander Rush. \emph{\href{ https://arxiv.org/abs/2409.12181 }{ A controlled study on long context extension and generalization in llms.} }\emph{ Preprint 2024 } \medskip -[4] \ind Zhiying Xu, Francis Y. Yan, Rachee Singh, Justin T. Chiu, Alexander M. Rush, Minlan Yu. \emph{\href{ https://arxiv.org/abs/2210.13763 }{ Teal: Learning-Accelerated Optimization of WAN Traffic Engineering.} }\emph{ SIGCOMM 2023 } +[4] \ind J. Wang, D. Paliotta, A. May, Alexander Rush, T. Dao. \emph{\href{ https://arxiv.org/abs/2408.15237 }{ The mamba in the llama: Distilling and accelerating hybrid models.} }\emph{ NeurIPS 2024 } \medskip -[5] \ind John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2310.06816.pdf }{ Text Embeddings Reveal (Almost) As Much As Text.} }\emph{ EMNLP 2023 } +[5] \ind S. Geng, W. Zhao, Alexander Rush. \emph{\href{ https://arxiv.org/abs/2408.11815 }{ Great Memory, Shallow Reasoning: Limits of NN-LMs.} }\emph{ Preprint 2024 } \medskip -[6] \ind John X. Morris, Chandan Singh, Alexander M. Rush, Jianfeng Gao, Yuntian Deng. \emph{\href{ https://arxiv.org/pdf/2310.14034.pdf }{ Tree Prompting: Efficient Task Adaptation without Fine-Tuning.} }\emph{ EMNLP 2023 } +[6] \ind J. N. Yan, T. Liu, J. Chiu, J. Shen, Z. Qin, Y. Yu, C. Lakshmanan, Y. Kurzion, Alexander Rush. \emph{\href{ https://aclanthology.org/2024.acl-long.839/ }{ Predicting text preference via structured comparative reasoning.} }\emph{ ACL 2024 } \medskip -[7] \ind Wenting Zhao, Justin T. Chiu, Claire Cardie, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2305.14237.pdf }{ HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervision.} }\emph{ EMNLP 2023 } +[7] \ind W. Zhao, G. Gao, C. Cardie, Alexander Rush. \emph{\href{ https://arxiv.org/abs/2407.17469 }{ I Could've Asked That: Reformulating Unanswerable Questions.} }\emph{ EMNLP 2024 } \medskip -[8] \ind Junxiong Wang, Jing Nathan Yan, Albert Gu, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2212.10544.pdf }{ Pretraining Without Attention.} }\emph{ EMNLP 2023 Findings } +[8] \ind Yash Akhauri, Ahmed F AbouElhamayed, Jordan Dotzel, Zhiru Zhang, Alexander M Rush, Safeen Huda, Mohamed S Abdelfattah. \emph{\href{ https://arxiv.org/abs/2406.16635 }{ ShadowLLM: Predictor-based Contextual Sparsity for Large Language Models.} }\emph{ EMNLP 2024 } \medskip -[9] \ind Niklas Muennighoff, Alexander M. Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, Colin Raffel. \emph{\href{ https://arxiv.org/pdf/2305.16264.pdf }{ Scaling Data-Constrained Language Models.} }\emph{ NeurIPS 2023 (Oral) } +[9] \ind Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, Aaron Gokaslan, Edgar Marroquin, Justin T Chiu, Alexander Rush, Volodymyr Kuleshov. \emph{\href{ https://arxiv.org/abs/2406.07524 }{ Simple and Effective Masked Diffusion Language Models.} }\emph{ NeurIPS 2024 } \medskip -[10] \ind Hugo Laurençon, Lucile Saulnier, Léo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov, Thomas Wang, Siddharth Karamcheti, Alexander M. Rush, Douwe Kiela, Matthieu Cord, Victor Sanh. \emph{\href{ https://arxiv.org/pdf/2306.16527.pdf }{ OBELISC: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents.} }\emph{ NeurIPS 2023 Dataset } +[10] \ind Junxiong Wang, Ali Mousavi, Omar Attia, Ronak Pradeep, Saloni Potdar, Alexander M Rush, Umar Farooq Minhas, Yunyao Li. \emph{\href{ https://arxiv.org/abs/2404.01626 }{ Entity disambiguation via fusion entity decoding.} }\emph{ NAACL 2024 } \medskip -[11] \ind Wenting Zhao, Justin T. Chiu, Claire Cardie, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2305.14618.pdf }{ Abductive Commonsense Reasoning Exploiting Mutually Exclusive Explanations.} }\emph{ ACL 2023 } +[11] \ind Junxiong Wang, Tushaar Gangavarapu, Jing Nathan Yan, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/2401.13660 }{ MambaByte: Token-free Selective State Space Model.} }\emph{ COLM 2024 } \medskip -[12] \ind Yuntian Deng, Noriyuki Kojima, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/2210.05147 }{ Markup-to-Image Diffusion Models with Scheduled Sampling.} }\emph{ ICLR 2023 } +[12] \ind Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, Thomas Wolf. \emph{\href{ https://arxiv.org/pdf/2310.16944.pdf }{ Zephyr: Direct Distillation of LM Alignment.} }\emph{ COLM 2024 } \medskip -[13] \ind Thierry Tambe, Jeff Zhang, Coleman Hooper, Tianyu Jia, Paul N. Whatmough, Joseph Zuckerman, Maico Cassel dos Santos, Erik Jens Loscalzo, Davide Giri, Kenneth L. Shepard, Luca P. Carloni, Alexander M. Rush, David Brooks, Gu-Yeon Wei. \emph{\href{ None }{ A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management.} }\emph{ ISSCC 2023 } +[13] \ind Celine Lee, Abdulrahman Mahmoud, Michal Kurek, Simone Campanoni, David Brooks, Stephen Chong, Gu-Yeon Wei, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2309.14396.pdf }{ Guess and Sketch: Language Model Guided Transpilation.} }\emph{ ICLR 2024 } \medskip -[14] \ind BigScience Workshop. \emph{\href{ https://arxiv.org/abs/2211.05100 }{ BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.} }\emph{ Arxiv Preprint } +[14] \ind Justin T. Chiu, Wenting Zhao, Derek Chen, Saujas Vaduguru, Alexander M. Rush, Daniel Fried. \emph{\href{ https://arxiv.org/pdf/2310.17140.pdf }{ Symbolic Planning and Code Generation for Grounded Dialogue.} }\emph{ EMNLP 2023 } \medskip -[15] \ind David Chiang, Alexander M. Rush, Boaz Barak. \emph{\href{ https://arxiv.org/pdf/2102.13196.pdf }{ Named Tensor Notation.} }\emph{ TMLR 2022 } +[15] \ind Zhiying Xu, Francis Y. Yan, Rachee Singh, Justin T. Chiu, Alexander M. Rush, Minlan Yu. \emph{\href{ https://arxiv.org/abs/2210.13763 }{ Teal: Learning-Accelerated Optimization of WAN Traffic Engineering.} }\emph{ SIGCOMM 2023 } \medskip -[16] \ind Zhiying Xu, Sivaramakrishnan Ramanathan, Alexander Rush, Jelena Mirkovic, Minlan Yu. \emph{\href{ https://dl.acm.org/doi/abs/10.1145/3555050.3569121 }{ Xatu: boosting existing DDoS detection systems using auxiliary signals.} }\emph{ CoNEXT 2022 } +[16] \ind John X. Morris, Volodymyr Kuleshov, Vitaly Shmatikov, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2310.06816.pdf }{ Text Embeddings Reveal (Almost) As Much As Text.} }\emph{ EMNLP 2023 } \medskip -[17] \ind John X Morris, Justin T Chiu, Ramin Zabih, Alexander M Rush. \emph{\href{ https://arxiv.org/pdf/2210.11528.pdf }{ Unsupervised Text Deidentification.} }\emph{ EMNLP Findings 2022 } +[17] \ind John X. Morris, Chandan Singh, Alexander M. Rush, Jianfeng Gao, Yuntian Deng. \emph{\href{ https://arxiv.org/pdf/2310.14034.pdf }{ Tree Prompting: Efficient Task Adaptation without Fine-Tuning.} }\emph{ EMNLP 2023 } \medskip -[18] \ind Yuntian Deng, Volodymyr Kuleshov, Alexander M Rush. \emph{\href{ https://arxiv.org/pdf/2210.08444.pdf }{ Model Criticism for Long-Form Text Generation.} }\emph{ EMNLP 2022 } +[18] \ind Wenting Zhao, Justin T. Chiu, Claire Cardie, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2305.14237.pdf }{ HOP, UNION, GENERATE: Explainable Multi-hop Reasoning without Rationale Supervision.} }\emph{ EMNLP 2023 } \medskip -[19] \ind Leandro von Werra et al.. \emph{\href{ https://arxiv.org/abs/2210.01970 }{ Evaluate and Evaluation on the Hub: Better Best Practices for Data and Model Measurement.} }\emph{ EMNLP Demos 2022 (Best Demo) } +[19] \ind Junxiong Wang, Jing Nathan Yan, Albert Gu, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2212.10544.pdf }{ Pretraining Without Attention.} }\emph{ EMNLP 2023 Findings } \medskip -[20] \ind Hendik Strobelt et al.. \emph{\href{ https://ieeexplore.ieee.org/abstract/document/9908590 }{ Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models.} }\emph{ IEEE Trans on Visualization 2022 } +[20] \ind Niklas Muennighoff, Alexander M. Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, Colin Raffel. \emph{\href{ https://arxiv.org/pdf/2305.16264.pdf }{ Scaling Data-Constrained Language Models.} }\emph{ NeurIPS 2023 (Oral) } \medskip -[21] \ind Thierry Tambe et al.. \emph{\href{ https://discovery.ucl.ac.uk/id/eprint/10150658/1/A_16-nm_SoC_for_Noise-Robust_Speech.pdf }{ A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs.} }\emph{ IEEE Solid-State Circuits 2022 } +[21] \ind Hugo Laurençon, Lucile Saulnier, Léo Tronchon, Stas Bekman, Amanpreet Singh, Anton Lozhkov, Thomas Wang, Siddharth Karamcheti, Alexander M. Rush, Douwe Kiela, Matthieu Cord, Victor Sanh. \emph{\href{ https://arxiv.org/pdf/2306.16527.pdf }{ OBELISC: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents.} }\emph{ NeurIPS 2023 Dataset } \medskip -[22] \ind Stephen Bach et al.. \emph{\href{ https://arxiv.org/abs/2202.01279 }{ Promptsource: An integrated development environment and repository for natural language prompts.} }\emph{ ACL Demo 2022 } +[22] \ind Wenting Zhao, Justin T. Chiu, Claire Cardie, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2305.14618.pdf }{ Abductive Commonsense Reasoning Exploiting Mutually Exclusive Explanations.} }\emph{ ACL 2023 } \medskip -[23] \ind Samantha Petti, et al.. \emph{\href{ http://repository.cshl.edu/id/eprint/40409/1/2021.Petti.multiple_sequence_alignments.pdf }{ End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman.} }\emph{ Bioinformatics } +[23] \ind Yuntian Deng, Noriyuki Kojima, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/2210.05147 }{ Markup-to-Image Diffusion Models with Scheduled Sampling.} }\emph{ ICLR 2023 } \medskip -[24] \ind Victor Sanh, et al.. \emph{\href{ https://arxiv.org/pdf/2110.08207 }{ Multitask prompted training enables zero-shot task generalization.} }\emph{ ICLR 2022 } +[24] \ind Thierry Tambe, Jeff Zhang, Coleman Hooper, Tianyu Jia, Paul N. Whatmough, Joseph Zuckerman, Maico Cassel dos Santos, Erik Jens Loscalzo, Davide Giri, Kenneth L. Shepard, Luca P. Carloni, Alexander M. Rush, David Brooks, Gu-Yeon Wei. \emph{\href{ None }{ A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication and Fine-Grained Power Management.} }\emph{ ISSCC 2023 } \medskip -[25] \ind Stanislav Lukyanenko et al.. \emph{\href{ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526069/ }{ Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field.} }\emph{ MICCAI 2021 } +[25] \ind BigScience Workshop. \emph{\href{ https://arxiv.org/abs/2211.05100 }{ BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.} }\emph{ Arxiv Preprint } \medskip -[26] \ind Keyon Vafa, Yuntian Deng, David Blei, Alexander Rush. \emph{\href{ https://arxiv.org/pdf/2109.06387 }{ Rationales for sequential predictions.} }\emph{ EMNLP 2021 } +[26] \ind David Chiang, Alexander M. Rush, Boaz Barak. \emph{\href{ https://arxiv.org/pdf/2102.13196.pdf }{ Named Tensor Notation.} }\emph{ TMLR 2022 } \medskip -[27] \ind Justin Chiu, Yuntian Deng, and Alexander M. Rush. \emph{\href{ https://proceedings.neurips.cc/paper/2021/file/16c0d78ef6a76b5c247113a4c9514059-Paper.pdf }{ Low-Rank Constraints for Fast Inference in Structured Models.} }\emph{ NeurIPS 2021 } +[27] \ind Zhiying Xu, Sivaramakrishnan Ramanathan, Alexander Rush, Jelena Mirkovic, Minlan Yu. \emph{\href{ https://dl.acm.org/doi/abs/10.1145/3555050.3569121 }{ Xatu: boosting existing DDoS detection systems using auxiliary signals.} }\emph{ CoNEXT 2022 } \medskip -[28] \ind Matthe Skiles et al.. \emph{\href{ https://www.nature.com/articles/s41893-021-00823-2 }{ Conference demographics and footprint changed by virtual platforms.} }\emph{ Nature Sustainability } +[28] \ind John X Morris, Justin T Chiu, Ramin Zabih, Alexander M Rush. \emph{\href{ https://arxiv.org/pdf/2210.11528.pdf }{ Unsupervised Text Deidentification.} }\emph{ EMNLP Findings 2022 } \medskip -[29] \ind Yuntian Deng and Alexander M. Rush. \emph{\href{ https://aclanthology.org/2021.findings-emnlp.318.pdf }{ Sequence-to-Lattice Models for Fast Translation.} }\emph{ EMNLP Findings Short 2021 } +[29] \ind Yuntian Deng, Volodymyr Kuleshov, Alexander M Rush. \emph{\href{ https://arxiv.org/pdf/2210.08444.pdf }{ Model Criticism for Long-Form Text Generation.} }\emph{ EMNLP 2022 } \medskip -[30] \ind Quentin Lhoest et al. \emph{\href{ https://arxiv.org/pdf/2109.02846.pdf }{ Datasets: A Community Library for Natural Language Processing.} }\emph{ EMNLP Demos 2021 (Best Demo) } +[30] \ind Leandro von Werra et al.. \emph{\href{ https://arxiv.org/abs/2210.01970 }{ Evaluate and Evaluation on the Hub: Better Best Practices for Data and Model Measurement.} }\emph{ EMNLP Demos 2022 (Best Demo) } \medskip -[31] \ind Thierry Tambe and Others. \emph{\href{ https://arxiv.org/pdf/2011.14203.pdf }{ EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference.} }\emph{ IEEE MICRO 2021 } +[31] \ind Hendik Strobelt et al.. \emph{\href{ https://ieeexplore.ieee.org/abstract/document/9908590 }{ Interactive and Visual Prompt Engineering for Ad-hoc Task Adaptation with Large Language Models.} }\emph{ IEEE Trans on Visualization 2022 } \medskip -[32] \ind Hendrik Strobelt, Jambay Kinley, Robert Krueger, Johanna Beyer, Alexander M. Rush, Hanspeter Pfister. \emph{\href{ None }{ GenNI: Human-AI Collaboration for Data-Backed Text Generation.} }\emph{ IEEE VIS 2021 } +[32] \ind Thierry Tambe et al.. \emph{\href{ https://discovery.ucl.ac.uk/id/eprint/10150658/1/A_16-nm_SoC_for_Noise-Robust_Speech.pdf }{ A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs.} }\emph{ IEEE Solid-State Circuits 2022 } \medskip -[33] \ind Demi Guo, Alexander M. Rush, Yoon Kim. \emph{\href{ https://arxiv.org/pdf/2012.07463.pdf }{ Parameter-efficient transfer learning with diff pruning.} }\emph{ ACL 2021 } +[33] \ind Stephen Bach et al.. \emph{\href{ https://arxiv.org/abs/2202.01279 }{ Promptsource: An integrated development environment and repository for natural language prompts.} }\emph{ ACL Demo 2022 } \medskip -[34] \ind Teven Le Scao, Alexander M. Rush. \emph{\href{ https://aclanthology.org/2021.naacl-main.208.pdf }{ How many data points is a prompt worth?.} }\emph{ NAACL Short 2021 (Best Paper - Runner-Up) } +[34] \ind Samantha Petti, et al.. \emph{\href{ http://repository.cshl.edu/id/eprint/40409/1/2021.Petti.multiple_sequence_alignments.pdf }{ End-to-end learning of multiple sequence alignments with differentiable Smith-Waterman.} }\emph{ Bioinformatics } \medskip -[35] \ind François Lagunas, Ella Charlaix, Victor Sanh, Alexander M Rush. \emph{\href{ https://arxiv.org/pdf/2109.04838 }{ Block pruning for faster transformers.} }\emph{ ACL 2021 } +[35] \ind Victor Sanh, et al.. \emph{\href{ https://arxiv.org/pdf/2110.08207 }{ Multitask prompted training enables zero-shot task generalization.} }\emph{ ICLR 2022 } \medskip -[36] \ind Steven Cao, Victor Sanh, Alexander M. Rush. \emph{\href{ https://aclanthology.org/2021.naacl-main.74/ }{ Low-Complexity Probing via Finding Subnetworks.} }\emph{ NAACL Short 2021 } +[36] \ind Stanislav Lukyanenko et al.. \emph{\href{ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526069/ }{ Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field.} }\emph{ MICCAI 2021 } \medskip -[37] \ind Xinya Du, Alexander M. Rush, Claire Cardie. \emph{\href{ https://aclanthology.org/2021.naacl-main.70/ }{ Template Filling with Generative Transformers.} }\emph{ NAACL Short 2021 } +[37] \ind Keyon Vafa, Yuntian Deng, David Blei, Alexander Rush. \emph{\href{ https://arxiv.org/pdf/2109.06387 }{ Rationales for sequential predictions.} }\emph{ EMNLP 2021 } \medskip -[38] \ind Thierry Tambe, En-Yu Yang, Glenn G Ko, Yuji Chai, Coleman Hooper, Marco Donato, Paul N Whatmough, Alexander M Rush, David Brooks, Gu-Yeon Wei. \emph{\href{ https://ieeexplore.ieee.org/abstract/document/9366062 }{ 9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET.} }\emph{ IEEE International Solid-State Circuits Conference 2021 } +[38] \ind Justin Chiu, Yuntian Deng, and Alexander M. Rush. \emph{\href{ https://proceedings.neurips.cc/paper/2021/file/16c0d78ef6a76b5c247113a4c9514059-Paper.pdf }{ Low-Rank Constraints for Fast Inference in Structured Models.} }\emph{ NeurIPS 2021 } \medskip -[39] \ind Yuntian Deng, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2006.01112 }{ Cascaded Text Generation with Markov Transformers.} }\emph{ NeurIPS 2020 } +[39] \ind Matthe Skiles et al.. \emph{\href{ https://www.nature.com/articles/s41893-021-00823-2 }{ Conference demographics and footprint changed by virtual platforms.} }\emph{ Nature Sustainability } \medskip -[40] \ind Yao Fu, Chuanqi Tan, Bin Bi, Mosha Chen, Yansong Feng, Alexander Rush. \emph{\href{ https://github.com/FranxYao/Gumbel-CRF }{ Latent Template Induction with Gumbel-CRFs.} }\emph{ NeurIPS 2020 } +[40] \ind Yuntian Deng and Alexander M. Rush. \emph{\href{ https://aclanthology.org/2021.findings-emnlp.318.pdf }{ Sequence-to-Lattice Models for Fast Translation.} }\emph{ EMNLP Findings Short 2021 } \medskip -[41] \ind Victor Sanh, Thomas Wolf, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2005.07683 }{ Movement Pruning: Adaptive Sparsity by Fine-Tuning.} }\emph{ NeurIPS 2020 } +[41] \ind Quentin Lhoest et al. \emph{\href{ https://arxiv.org/pdf/2109.02846.pdf }{ Datasets: A Community Library for Natural Language Processing.} }\emph{ EMNLP Demos 2021 (Best Demo) } \medskip -[42] \ind Justin T. Chiu, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/2011.04640 }{ Scaling Hidden Markov Language Models.} }\emph{ EMNLP 2020 } +[42] \ind Thierry Tambe and Others. \emph{\href{ https://arxiv.org/pdf/2011.14203.pdf }{ EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference.} }\emph{ IEEE MICRO 2021 } \medskip -[43] \ind Congzheng Song, Alexander M. Rush, Vitaly Shmatikov. \emph{\href{ https://www.cs.cornell.edu/~shmat/shmat_emnlp20.pdf }{ Adversarial Semantic Collisions.} }\emph{ EMNLP 2020 } +[43] \ind Hendrik Strobelt, Jambay Kinley, Robert Krueger, Johanna Beyer, Alexander M. Rush, Hanspeter Pfister. \emph{\href{ None }{ GenNI: Human-AI Collaboration for Data-Backed Text Generation.} }\emph{ IEEE VIS 2021 } \medskip -[44] \ind Demi Guo, Yoon Kim, Alexander M. Rush. \emph{\href{ https://www.aclweb.org/anthology/2020.emnlp-main.447/ }{ Sequence-Level Mixed Sample Data Augmentation.} }\emph{ EMNLP 2020 } +[44] \ind Demi Guo, Alexander M. Rush, Yoon Kim. \emph{\href{ https://arxiv.org/pdf/2012.07463.pdf }{ Parameter-efficient transfer learning with diff pruning.} }\emph{ ACL 2021 } \medskip -[45] \ind Thierry Tambe, En-Yu Yang, Zishen Wan, Yuntian Deng, Vijay Janapa Reddi, Alexander Rush, David Brooks, Gu-Yeon Wei. \emph{\href{ https://arxiv.org/pdf/1909.13271 }{ AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference.} }\emph{ DAC 2020 (Best Paper) } +[45] \ind Teven Le Scao, Alexander M. Rush. \emph{\href{ https://aclanthology.org/2021.naacl-main.208.pdf }{ How many data points is a prompt worth?.} }\emph{ NAACL Short 2021 (Best Paper - Runner-Up) } \medskip -[46] \ind Thomas Wolf et al. \emph{\href{ https://arxiv.org/pdf/1910.03771 }{ Transformers: State-of-the-art Natural Language Processing.} }\emph{ EMNLP Demos 2020 (Best Demo) } +[46] \ind François Lagunas, Ella Charlaix, Victor Sanh, Alexander M Rush. \emph{\href{ https://arxiv.org/pdf/2109.04838 }{ Block pruning for faster transformers.} }\emph{ ACL 2021 } \medskip -[47] \ind Alexander Rush. \emph{\href{ https://arxiv.org/pdf/2002.00876 }{ Torch-Struct: Deep Structured Prediction Library.} }\emph{ ACL Demos 2020 (Best Demo Honorable Mention) } +[47] \ind Steven Cao, Victor Sanh, Alexander M. Rush. \emph{\href{ https://aclanthology.org/2021.naacl-main.74/ }{ Low-Complexity Probing via Finding Subnetworks.} }\emph{ NAACL Short 2021 } \medskip -[48] \ind Noriyuki Kojima, Hadar Averbuch-Elor, Alexander M. Rush, Yoav Artzi. \emph{\href{ https://arxiv.org/pdf/2005.01678 }{ What is Learned in Visually Grounded Neural Syntax Acquisition.} }\emph{ ACL 2020 (Short) } +[48] \ind Xinya Du, Alexander M. Rush, Claire Cardie. \emph{\href{ https://aclanthology.org/2021.naacl-main.70/ }{ Template Filling with Generative Transformers.} }\emph{ NAACL Short 2021 } \medskip -[49] \ind Xiang Lisa Li, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2005.04560 }{ Posterior Control of Blackbox Generation.} }\emph{ ACL 2020 } +[49] \ind Thierry Tambe, En-Yu Yang, Glenn G Ko, Yuji Chai, Coleman Hooper, Marco Donato, Paul N Whatmough, Alexander M Rush, David Brooks, Gu-Yeon Wei. \emph{\href{ https://ieeexplore.ieee.org/abstract/document/9366062 }{ 9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET.} }\emph{ IEEE International Solid-State Circuits Conference 2021 } \medskip -[50] \ind Jiawei Zhou, Zhiying Xu, Alexander M. Rush, Minlan Yu. \emph{\href{ https://arxiv.org/pdf/2003.06344 }{ Automating Botnet Detection with Graph Neural Networks.} }\emph{ AutoML for Networking and Systems Workshop } +[50] \ind Yuntian Deng, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2006.01112 }{ Cascaded Text Generation with Markov Transformers.} }\emph{ NeurIPS 2020 } \medskip -[51] \ind Georgios A. Tritsaris, Yiqi Xie, Alexander M. Rush, Stephen Carr, Marios Mattheakis, Efthimios Kaxiras. \emph{\href{ https://arxiv.org/pdf/1910.03413 }{ LAN -- A materials notation for 2D layered assemblies.} }\emph{ None } +[51] \ind Yao Fu, Chuanqi Tan, Bin Bi, Mosha Chen, Yansong Feng, Alexander Rush. \emph{\href{ https://github.com/FranxYao/Gumbel-CRF }{ Latent Template Induction with Gumbel-CRFs.} }\emph{ NeurIPS 2020 } \medskip -[52] \ind Udit Gupta, Brandon Reagen, Lillian Pentecost, Marco Donato, Thierry Tambe, Alexander M. Rush, Gu-Yeon Wei, David Brooks. \emph{\href{ None }{ MASR: A Modular Accelerator for Sparse RNNs.} }\emph{ PACT 2019 } +[52] \ind Victor Sanh, Thomas Wolf, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2005.07683 }{ Movement Pruning: Adaptive Sparsity by Fine-Tuning.} }\emph{ NeurIPS 2020 } \medskip -[53] \ind Joe Davison, Joshua Feldman and Alexander Rush. \emph{\href{ None }{ Commonsense Knowledge Mining from Pretrained Models.} }\emph{ EMNLP 2019 } +[53] \ind Justin T. Chiu, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/2011.04640 }{ Scaling Hidden Markov Language Models.} }\emph{ EMNLP 2020 } \medskip -[54] \ind Zachary Ziegler, Yuntian Deng and Alexander Rush. \emph{\href{ https://arxiv.org/abs/1909.01496 }{ Neural Linguistic Steganography.} }\emph{ EMNLP 2019 } +[54] \ind Congzheng Song, Alexander M. Rush, Vitaly Shmatikov. \emph{\href{ https://www.cs.cornell.edu/~shmat/shmat_emnlp20.pdf }{ Adversarial Semantic Collisions.} }\emph{ EMNLP 2020 } \medskip -[55] \ind Yoon Kim, Chris Dyer, Alexander M. Rush. \emph{\href{ https://www.aclweb.org/anthology/P19-1228/ }{ Compound Probabilistic Context-Free Grammars for Grammar Induction.} }\emph{ ACL 2019 } +[55] \ind Demi Guo, Yoon Kim, Alexander M. Rush. \emph{\href{ https://www.aclweb.org/anthology/2020.emnlp-main.447/ }{ Sequence-Level Mixed Sample Data Augmentation.} }\emph{ EMNLP 2020 } \medskip -[56] \ind Gehrmann S, Strobelt H, Krueger R, Pfister H, and Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1907.10739 }{ Visual Interaction with Deep Learning Models through Collaborative Semantic Inference.} }\emph{ InfoVis 2019 } +[56] \ind Thierry Tambe, En-Yu Yang, Zishen Wan, Yuntian Deng, Vijay Janapa Reddi, Alexander Rush, David Brooks, Gu-Yeon Wei. \emph{\href{ https://arxiv.org/pdf/1909.13271 }{ AdaptivFloat: A Floating-point based Data Type for Resilient Deep Learning Inference.} }\emph{ DAC 2020 (Best Paper) } \medskip -[57] \ind Jiawei Zhou, Alexander M. Rush. \emph{\href{ https://www.aclweb.org/anthology/P19-1503 }{ Simple Unsupervised Summarization by Contextual Matching.} }\emph{ ACL 2019 } +[57] \ind Thomas Wolf et al. \emph{\href{ https://arxiv.org/pdf/1910.03771 }{ Transformers: State-of-the-art Natural Language Processing.} }\emph{ EMNLP Demos 2020 (Best Demo) } \medskip -[58] \ind Sebastian Gehrmann, Hendrik Strobelt, Alexander M Rush. \emph{\href{ https://arxiv.org/abs/1906.04043 }{ GLTR: Statistical Detection and Visualization of Generated Text.} }\emph{ ACL Demo 2019 (Best Demo Honorable Mention) } +[58] \ind Alexander Rush. \emph{\href{ https://arxiv.org/pdf/2002.00876 }{ Torch-Struct: Deep Structured Prediction Library.} }\emph{ ACL Demos 2020 (Best Demo Honorable Mention) } \medskip -[59] \ind Yoon Kim, Alexander M. Rush, Lei Yu, Adhiguna Kuncoro, Chris Dyer, Gabor Melis. \emph{\href{ https://arxiv.org/pdf/1904.03746.pdf }{ Unsupervised Recurrent Neural Network Grammars.} }\emph{ NAACL 2019 } +[59] \ind Noriyuki Kojima, Hadar Averbuch-Elor, Alexander M. Rush, Yoav Artzi. \emph{\href{ https://arxiv.org/pdf/2005.01678 }{ What is Learned in Visually Grounded Neural Syntax Acquisition.} }\emph{ ACL 2020 (Short) } \medskip -[60] \ind Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei. \emph{\href{ https://arxiv.org/pdf/1807.04863.pdf }{ Avoiding Latent Variable Collapse With Generative Skip Models.} }\emph{ AISTATS 2019 } +[60] \ind Xiang Lisa Li, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/2005.04560 }{ Posterior Control of Blackbox Generation.} }\emph{ ACL 2020 } \medskip -[61] \ind Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin Chiu, Neeraj Pradhan, Alexander Rush, Noah Goodman. \emph{\href{ https://arxiv.org/pdf/1902.03210.pdf }{ Tensor Variable Elimination for Plated Factor Graphs.} }\emph{ ICML 2019 } +[61] \ind Jiawei Zhou, Zhiying Xu, Alexander M. Rush, Minlan Yu. \emph{\href{ https://arxiv.org/pdf/2003.06344 }{ Automating Botnet Detection with Graph Neural Networks.} }\emph{ AutoML for Networking and Systems Workshop } \medskip -[62] \ind Zachary M. Ziegler, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/1901.10548 }{ Latent Normalizing Flows for Discrete Sequences.} }\emph{ ICML 2019 } +[62] \ind Georgios A. Tritsaris, Yiqi Xie, Alexander M. Rush, Stephen Carr, Marios Mattheakis, Efthimios Kaxiras. \emph{\href{ https://arxiv.org/pdf/1910.03413 }{ LAN -- A materials notation for 2D layered assemblies.} }\emph{ None } \medskip -[63] \ind Yoon Kim, Sam Wiseman, Alexander M. Rush. \emph{\href{ https://github.com/harvardnlp/DeepLatentNLP/raw/master/tutorial_deep_latent.pdf }{ Deep Latent-Variable Models for Natural Language.} }\emph{ EMNLP 2018 (Tutorial) } +[63] \ind Udit Gupta, Brandon Reagen, Lillian Pentecost, Marco Donato, Thierry Tambe, Alexander M. Rush, Gu-Yeon Wei, David Brooks. \emph{\href{ None }{ MASR: A Modular Accelerator for Sparse RNNs.} }\emph{ PACT 2019 } \medskip -[64] \ind Sebastian Gehrmann, Falcon Z. Dai, Henry Elder, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/1810.04700 }{ End-to-End Content and Plan Selection for Data-to-Text Generation.} }\emph{ INLG 2018 } +[64] \ind Joe Davison, Joshua Feldman and Alexander Rush. \emph{\href{ None }{ Commonsense Knowledge Mining from Pretrained Models.} }\emph{ EMNLP 2019 } \medskip -[65] \ind Yuntian Deng*, Yoon Kim*, Justin Chiu, Demi Guo, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/1807.03756.pdf }{ Latent Alignment and Variational Attention.} }\emph{ NIPS 2018 } +[65] \ind Zachary Ziegler, Yuntian Deng and Alexander Rush. \emph{\href{ https://arxiv.org/abs/1909.01496 }{ Neural Linguistic Steganography.} }\emph{ EMNLP 2019 } \medskip -[66] \ind Sam Wiseman, Stuart M. Shieber, Alexander Rush. \emph{\href{ https://arxiv.org/abs/1808.10122 }{ Learning Neural Templates for Text Generation.} }\emph{ EMNLP 2018 } +[66] \ind Yoon Kim, Chris Dyer, Alexander M. Rush. \emph{\href{ https://www.aclweb.org/anthology/P19-1228/ }{ Compound Probabilistic Context-Free Grammars for Grammar Induction.} }\emph{ ACL 2019 } \medskip -[67] \ind Sebastian Gehrmann, Yuntian Deng, Alexander Rush. \emph{\href{ https://arxiv.org/abs/1808.10792 }{ Bottom-Up Abstractive Summarization.} }\emph{ EMNLP 2018 } +[67] \ind Gehrmann S, Strobelt H, Krueger R, Pfister H, and Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1907.10739 }{ Visual Interaction with Deep Learning Models through Collaborative Semantic Inference.} }\emph{ InfoVis 2019 } \medskip -[68] \ind Luke Melas-Kyriazi, George Han, Alexander Rush. \emph{\href{ https://www.aclweb.org/anthology/D18-1084 }{ Training for Diversity in Image Paragraph Captioning.} }\emph{ EMNLP 2018 (Short) } +[68] \ind Jiawei Zhou, Alexander M. Rush. \emph{\href{ https://www.aclweb.org/anthology/P19-1503 }{ Simple Unsupervised Summarization by Contextual Matching.} }\emph{ ACL 2019 } \medskip -[69] \ind Luong Hoang, Sam Wiseman, Alexander Rush. \emph{\href{ https://www.aclweb.org/anthology/D18-1130 }{ Entity Tracking Improves Cloze-style Reading Comprehension.} }\emph{ EMNLP 2018 (Short) } +[69] \ind Sebastian Gehrmann, Hendrik Strobelt, Alexander M Rush. \emph{\href{ https://arxiv.org/abs/1906.04043 }{ GLTR: Statistical Detection and Visualization of Generated Text.} }\emph{ ACL Demo 2019 (Best Demo Honorable Mention) } \medskip -[70] \ind Hendrik Strobelt, Sebastian Gehrmann, Michael Behrisch, Adam Perer, Hanspeter Pfister, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1804.09299 }{ Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models .} }\emph{ VAST 2018, EMNLP-BlackBox 2018 (Best Paper - Honorable Mention) } +[70] \ind Yoon Kim, Alexander M. Rush, Lei Yu, Adhiguna Kuncoro, Chris Dyer, Gabor Melis. \emph{\href{ https://arxiv.org/pdf/1904.03746.pdf }{ Unsupervised Recurrent Neural Network Grammars.} }\emph{ NAACL 2019 } \medskip -[71] \ind Alexander M. Rush. \emph{\href{ http://aclweb.org/anthology/W18-2509 }{ The Annotated Transformer.} }\emph{ ACL NLP-OSS 2018 } +[71] \ind Adji B. Dieng, Yoon Kim, Alexander M. Rush, David M. Blei. \emph{\href{ https://arxiv.org/pdf/1807.04863.pdf }{ Avoiding Latent Variable Collapse With Generative Skip Models.} }\emph{ AISTATS 2019 } \medskip -[72] \ind Jean Senellart, Dakun Zhang, Bo Wang, Guillaume Klein, J.P. Ramatchandirin, Josep Crego, Alexander M. Rush. \emph{\href{ http://aclweb.org/anthology/W18-2715 }{ OpenNMT System Description for WNMT 2018: 800 words/sec on a single-core CPU.} }\emph{ WNMT 2018 (First-Place CPU Speed/Memory) } +[72] \ind Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin Chiu, Neeraj Pradhan, Alexander Rush, Noah Goodman. \emph{\href{ https://arxiv.org/pdf/1902.03210.pdf }{ Tensor Variable Elimination for Plated Factor Graphs.} }\emph{ ICML 2019 } \medskip -[73] \ind Yoon Kim, Sam Wiseman, Andrew C. Miller, David Sontag, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1802.02550 }{ Semi-Amortized Variational Autoencoders.} }\emph{ ICML 2018 } +[73] \ind Zachary M. Ziegler, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/1901.10548 }{ Latent Normalizing Flows for Discrete Sequences.} }\emph{ ICML 2019 } \medskip -[74] \ind Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks. \emph{\href{ https://www.sysml.cc/doc/68.pdf }{ Compressing Deep Neural Networks with Probabilistic Data Structures.} }\emph{ ICML 2018, SysML 2018 } +[74] \ind Yoon Kim, Sam Wiseman, Alexander M. Rush. \emph{\href{ https://github.com/harvardnlp/DeepLatentNLP/raw/master/tutorial_deep_latent.pdf }{ Deep Latent-Variable Models for Natural Language.} }\emph{ EMNLP 2018 (Tutorial) } \medskip -[75] \ind Allen Schmaltz, Yoon Kim, Alexander M. Rush, Stuart M. Shieber. \emph{\href{ https://arxiv.org/abs/1707.09067 }{ Adapting Sequence Models for Sentence Correction.} }\emph{ EMNLP 2017 } +[75] \ind Sebastian Gehrmann, Falcon Z. Dai, Henry Elder, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/1810.04700 }{ End-to-End Content and Plan Selection for Data-to-Text Generation.} }\emph{ INLG 2018 } \medskip -[76] \ind Sam Wiseman, Stuart M Shieber Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1707.08052 }{ Challenges in Data-to-Document Generation.} }\emph{ EMNLP 2017 } +[76] \ind Yuntian Deng*, Yoon Kim*, Justin Chiu, Demi Guo, Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/1807.03756.pdf }{ Latent Alignment and Variational Attention.} }\emph{ NIPS 2018 } \medskip -[77] \ind Junbo Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, Yann LeCun. \emph{\href{ https://arxiv.org/abs/1706.04223 }{ Adversarially Regularized Autoencoders.} }\emph{ ICML 2018, NIPS 2017 Workshop } +[77] \ind Sam Wiseman, Stuart M. Shieber, Alexander Rush. \emph{\href{ https://arxiv.org/abs/1808.10122 }{ Learning Neural Templates for Text Generation.} }\emph{ EMNLP 2018 } \medskip -[78] \ind Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1701.02810 }{ OpenNMT: Open-Source Toolkit for Neural Machine Translation.} }\emph{ ACL Demo 2017 (Best Demo Runner-up) } +[78] \ind Sebastian Gehrmann, Yuntian Deng, Alexander Rush. \emph{\href{ https://arxiv.org/abs/1808.10792 }{ Bottom-Up Abstractive Summarization.} }\emph{ EMNLP 2018 } \medskip -[79] \ind Ankit Gupta, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1710.01278 }{ Dilated Convolutions for Modeling Long-Distance Genomic Dependencies.} }\emph{ ICML CompBio 2017 (Best Poster) } +[79] \ind Luke Melas-Kyriazi, George Han, Alexander Rush. \emph{\href{ https://www.aclweb.org/anthology/D18-1084 }{ Training for Diversity in Image Paragraph Captioning.} }\emph{ EMNLP 2018 (Short) } \medskip -[80] \ind Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, and Alexander M. Rush. \emph{\href{ http://lstm.seas.harvard.edu/latex/ }{ Image-to-Markup Generation with Coarse-to-Fine Attention.} }\emph{ ICML 2017 } +[80] \ind Luong Hoang, Sam Wiseman, Alexander Rush. \emph{\href{ https://www.aclweb.org/anthology/D18-1130 }{ Entity Tracking Improves Cloze-style Reading Comprehension.} }\emph{ EMNLP 2018 (Short) } \medskip -[81] \ind Hendrik Strobelt, Sebastian Gehrmann, Hanspeter Pfister, and Alexander M. Rush. \emph{\href{ http://lstm.seas.harvard.edu/ }{ LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks.} }\emph{ InfoVis 2017 } +[81] \ind Hendrik Strobelt, Sebastian Gehrmann, Michael Behrisch, Adam Perer, Hanspeter Pfister, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1804.09299 }{ Seq2Seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models .} }\emph{ VAST 2018, EMNLP-BlackBox 2018 (Best Paper - Honorable Mention) } \medskip -[82] \ind Yoon Kim, Carl Denton, Luong Hoang, and Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1702.00887 }{ Structured Attention Networks.} }\emph{ ICLR 2017 } +[82] \ind Alexander M. Rush. \emph{\href{ http://aclweb.org/anthology/W18-2509 }{ The Annotated Transformer.} }\emph{ ACL NLP-OSS 2018 } \medskip -[83] \ind Greg Yang and Alexander M. Rush. \emph{\href{ http://lstm.seas.harvard.edu/lantm/ }{ Lie-Access Neural Turing Machines.} }\emph{ ICLR 2017 } +[83] \ind Jean Senellart, Dakun Zhang, Bo Wang, Guillaume Klein, J.P. Ramatchandirin, Josep Crego, Alexander M. Rush. \emph{\href{ http://aclweb.org/anthology/W18-2715 }{ OpenNMT System Description for WNMT 2018: 800 words/sec on a single-core CPU.} }\emph{ WNMT 2018 (First-Place CPU Speed/Memory) } \medskip -[84] \ind Yoon Kim and Alexander M. Rush. \emph{\href{ http://arxiv.org/pdf/1606.07947v1.pdf }{ Sequence-Level Knowledge Distillation.} }\emph{ EMNLP 2016 } +[84] \ind Yoon Kim, Sam Wiseman, Andrew C. Miller, David Sontag, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1802.02550 }{ Semi-Amortized Variational Autoencoders.} }\emph{ ICML 2018 } \medskip -[85] \ind Sam Wiseman and Alexander M. Rush. \emph{\href{ http://arxiv.org/pdf/1606.02960.pdf }{ Sequence-to-Sequence Learning as Beam-Search Optimization.} }\emph{ EMNLP 2016 (Best Paper Runner-Up) } +[85] \ind Brandon Reagen, Udit Gupta, Robert Adolf, Michael M. Mitzenmacher, Alexander M. Rush, Gu-Yeon Wei, David Brooks. \emph{\href{ https://www.sysml.cc/doc/68.pdf }{ Compressing Deep Neural Networks with Probabilistic Data Structures.} }\emph{ ICML 2018, SysML 2018 } \medskip -[86] \ind Peter Kraft, Hirsh Jain, and Alexander M. Rush. \emph{\href{ https://www.aclweb.org/anthology/D/D16/D16-1221.pdf }{ An Embedding Model for Predicting Roll-Call Votes.} }\emph{ Proceedings of EMNLP 2016 } +[86] \ind Allen Schmaltz, Yoon Kim, Alexander M. Rush, Stuart M. Shieber. \emph{\href{ https://arxiv.org/abs/1707.09067 }{ Adapting Sequence Models for Sentence Correction.} }\emph{ EMNLP 2017 } \medskip -[87] \ind Allen Schmaltz, Alexander M. Rush, and Stuart M. Shieber. \emph{\href{ https://arxiv.org/abs/1604.08633 }{ Word Ordering Without Syntax.} }\emph{ EMNLP 2016 } +[87] \ind Sam Wiseman, Stuart M Shieber Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1707.08052 }{ Challenges in Data-to-Document Generation.} }\emph{ EMNLP 2017 } \medskip -[88] \ind Allen Schmaltz, Yoon Kim, Alexander M. Rush, and Stuart M. Shieber. \emph{\href{ /papers/aesw2016.pdf }{ Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction.} }\emph{ Workshop Submission for AESW 2016 (Top Performing System) } +[88] \ind Junbo Zhao, Yoon Kim, Kelly Zhang, Alexander M. Rush, Yann LeCun. \emph{\href{ https://arxiv.org/abs/1706.04223 }{ Adversarially Regularized Autoencoders.} }\emph{ ICML 2018, NIPS 2017 Workshop } \medskip -[89] \ind Sam Wiseman, Alexander M. Rush, and Stuart M. Shieber. \emph{\href{ /papers/corefmain.pdf }{ Learning Global Features for Coreference Resolution.} }\emph{ NAACL 2016 } +[89] \ind Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1701.02810 }{ OpenNMT: Open-Source Toolkit for Neural Machine Translation.} }\emph{ ACL Demo 2017 (Best Demo Runner-up) } \medskip -[90] \ind Sumit Chopra, Michael Auli, and Alexander M. Rush. \emph{\href{ /papers/naacl16_summary.pdf }{ Abstractive Sentence Summarization with Attentive Recurrent Neural Networks.} }\emph{ NAACL 2016 } +[90] \ind Ankit Gupta, Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1710.01278 }{ Dilated Convolutions for Modeling Long-Distance Genomic Dependencies.} }\emph{ ICML CompBio 2017 (Best Poster) } \medskip -[91] \ind Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/1508.06615v4 }{ Character-Aware Neural Language Models.} }\emph{ AAAI 2016 } +[91] \ind Yuntian Deng, Anssi Kanervisto, Jeffrey Ling, and Alexander M. Rush. \emph{\href{ http://lstm.seas.harvard.edu/latex/ }{ Image-to-Markup Generation with Coarse-to-Fine Attention.} }\emph{ ICML 2017 } \medskip -[92] \ind Alexander M. Rush, Sumit Chopra, and Jason Weston. \emph{\href{ http://arxiv.org/pdf/1509.00685.pdf }{ A Neural Attention Model for Abstractive Sentence Summarization.} }\emph{ EMNLP 2015. } +[92] \ind Hendrik Strobelt, Sebastian Gehrmann, Hanspeter Pfister, and Alexander M. Rush. \emph{\href{ http://lstm.seas.harvard.edu/ }{ LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks.} }\emph{ InfoVis 2017 } \medskip -[93] \ind Jason Weston, Antoine Bordes, Sumit Chopra, Tomas Mikolov, and Alexander M. Rush. \emph{\href{ http://arxiv.org/pdf/1502.05698.pdf }{ Towards AI-Complete Question Answering A Set of Prerequisite Toy Tasks.} }\emph{ ArXiv Preprint } +[93] \ind Yoon Kim, Carl Denton, Luong Hoang, and Alexander M. Rush. \emph{\href{ https://arxiv.org/abs/1702.00887 }{ Structured Attention Networks.} }\emph{ ICLR 2017 } \medskip -[94] \ind Sam Wiseman, Alexander M. Rush, Jason Weston, and Stuart M. Shieber. \emph{\href{ http://people.seas.harvard.edu/~srush/acl15.pdf }{ Learning Anaphoricity and Antecedent Ranking Features for Coreference Resolution.} }\emph{ ACL 2015. } +[94] \ind Greg Yang and Alexander M. Rush. \emph{\href{ http://lstm.seas.harvard.edu/lantm/ }{ Lie-Access Neural Turing Machines.} }\emph{ ICLR 2017 } \medskip -[95] \ind Yacine Jernite, Alexander M. Rush, and David Sontag. \emph{\href{ http://people.seas.harvard.edu/~srush/icml15.pdf }{ A Fast Variational Approach for Learning Markov Random Field Language Models.} }\emph{ ICML 2015. } +[95] \ind Yoon Kim and Alexander M. Rush. \emph{\href{ http://arxiv.org/pdf/1606.07947v1.pdf }{ Sequence-Level Knowledge Distillation.} }\emph{ EMNLP 2016 } \medskip -[96] \ind Lingpeng Kong, Alexander M. Rush, and Noah A. Smith. \emph{\href{ http://people.seas.harvard.edu/~srush/naacl15.pdf }{ Transforming Dependencies into Phrase Structures.} }\emph{ NAACL 2015. } +[96] \ind Sam Wiseman and Alexander M. Rush. \emph{\href{ http://arxiv.org/pdf/1606.02960.pdf }{ Sequence-to-Sequence Learning as Beam-Search Optimization.} }\emph{ EMNLP 2016 (Best Paper Runner-Up) } \medskip +[97] \ind Peter Kraft, Hirsh Jain, and Alexander M. Rush. \emph{\href{ https://www.aclweb.org/anthology/D/D16/D16-1221.pdf }{ An Embedding Model for Predicting Roll-Call Votes.} }\emph{ Proceedings of EMNLP 2016 } +\medskip + + +[98] \ind Allen Schmaltz, Alexander M. Rush, and Stuart M. Shieber. \emph{\href{ https://arxiv.org/abs/1604.08633 }{ Word Ordering Without Syntax.} }\emph{ EMNLP 2016 } + +\medskip + + +[99] \ind Allen Schmaltz, Yoon Kim, Alexander M. Rush, and Stuart M. Shieber. \emph{\href{ /papers/aesw2016.pdf }{ Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction.} }\emph{ Workshop Submission for AESW 2016 (Top Performing System) } + +\medskip + + +[100] \ind Sam Wiseman, Alexander M. Rush, and Stuart M. Shieber. \emph{\href{ /papers/corefmain.pdf }{ Learning Global Features for Coreference Resolution.} }\emph{ NAACL 2016 } + +\medskip + + +[101] \ind Sumit Chopra, Michael Auli, and Alexander M. Rush. \emph{\href{ /papers/naacl16_summary.pdf }{ Abstractive Sentence Summarization with Attentive Recurrent Neural Networks.} }\emph{ NAACL 2016 } + +\medskip + + +[102] \ind Yoon Kim, Yacine Jernite, David Sontag, and Alexander M. Rush. \emph{\href{ https://arxiv.org/pdf/1508.06615v4 }{ Character-Aware Neural Language Models.} }\emph{ AAAI 2016 } + +\medskip + + +[103] \ind Alexander M. Rush, Sumit Chopra, and Jason Weston. \emph{\href{ http://arxiv.org/pdf/1509.00685.pdf }{ A Neural Attention Model for Abstractive Sentence Summarization.} }\emph{ EMNLP 2015. } + +\medskip -[97] \ind Yin-Wen Chang, Alexander M. Rush, John DeNero, and Michael Collins.. \emph{\href{ http://people.csail.mit.edu/srush/ }{ A Lagrangian Relaxation Algorithm for Bilingual Word Alignment.} }\emph{ Proceedings of ACL 2014. } -[98] \ind Alexander M. Rush, Yin-Wen Chang, and Michael Collins.. \emph{\href{ None }{ Optimal Beam Search for Machine Translation.} }\emph{ Proceedings of EMNLP 2013. } +[104] \ind Jason Weston, Antoine Bordes, Sumit Chopra, Tomas Mikolov, and Alexander M. Rush. \emph{\href{ http://arxiv.org/pdf/1502.05698.pdf }{ Towards AI-Complete Question Answering A Set of Prerequisite Toy Tasks.} }\emph{ ArXiv Preprint } + +\medskip -[99] \ind Karl Stratos, Alexander M. Rush, Shay B. Cohen, and Michael Collins.. \emph{\href{ http://www.cs.columbia.edu/~stratos/research/conll13rhmm.pdf }{ Spectral Learning of Refinement HMMs.} }\emph{ Proceedings of CoNLL 2013. } -[100] \ind Alexander M. Rush, Roi Reichert, Michael Collins, and Amir Globerson.. \emph{\href{ http://people.csail.mit.edu/srush/emnlp2012.pdf.pdf }{ Improved Parsing and POS Tagging Using Inter-Sentence Consistency Constraints.} }\emph{ Proceedings of EMNLP 2012. } +[105] \ind Sam Wiseman, Alexander M. Rush, Jason Weston, and Stuart M. Shieber. \emph{\href{ http://people.seas.harvard.edu/~srush/acl15.pdf }{ Learning Anaphoricity and Antecedent Ranking Features for Coreference Resolution.} }\emph{ ACL 2015. } -[101] \ind Alexander M. Rush and Slav Petrov. \emph{\href{ http://people.csail.mit.edu/srush/vine-paper.pdf }{ Vine Pruning for Efficient Multi-Pass Dependency Parsing.} }\emph{ Proceedings of NAACL 2012. (Best Paper Award) } +\medskip -[102] \ind Alexander M. Rush and Michael Collins.. \emph{\href{ http://people.csail.mit.edu/srush/exdecmt.pdf }{ Exact Decoding of Syntactic Translation Models through Lagrangian Relaxation.} }\emph{ Proceedings of ACL 2011. } -[103] \ind Terry Koo, Alexander M. Rush, Michael Collins, Tommi Jaakkola, and David Sontag.. \emph{\href{ http://people.csail.mit.edu/maestro/papers/koo10mstdd.pdf }{ Dual Decomposition for Parsing with Non-Projective Head Automata.} }\emph{ Proceedings of EMNLP 2010. } +[106] \ind Yacine Jernite, Alexander M. Rush, and David Sontag. \emph{\href{ http://people.seas.harvard.edu/~srush/icml15.pdf }{ A Fast Variational Approach for Learning Markov Random Field Language Models.} }\emph{ ICML 2015. } + +\medskip + + +[107] \ind Lingpeng Kong, Alexander M. Rush, and Noah A. Smith. \emph{\href{ http://people.seas.harvard.edu/~srush/naacl15.pdf }{ Transforming Dependencies into Phrase Structures.} }\emph{ NAACL 2015. } + +\medskip + -[104] \ind Alexander M. Rush, David Sontag, Michael Collins, and Tommi Jaakkola. \emph{\href{ http://people.csail.mit.edu/dsontag/papers/RusSonColJaa_emnlp10.pdf }{ On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing.} }\emph{ Proceedings of EMNLP 2010. } -[105] \ind Rebecca Nesson, Stuart M. Shieber, and Alexander M. Rush.. \emph{\href{ http://www.eecs.harvard.edu/~shieber/Biblio/Papers/Nesson-2006-IPS.pdf }{ Induction of probabilistic synchronous tree-insertion grammars for machine translation.} }\emph{ Proceedings of AMTA 2006. } \vspace{0.3in} @@ -810,6 +847,9 @@ \bigskip +\ind President / Founder : +\ind COLM 2024- + \ind Secretary: \ind ICLR Board 2021-2024 @@ -837,38 +877,27 @@ \ind PhD Students -\ind Graduated Harvard Students +\ind Graduated Students \begin{itemize} -\item Sam Wiseman (2019); Assistant Professor, Duke University -\item Yoon Kim (2020); Assistant Professor, MIT -\item Sebastian Gehrmann (2020); Google NLP + \item Justin Chiu (2024); Cohere AI + \item Jiawei Zhou (2023); Assistant Professor, Stonybrook + \item Yuntian Deng (2023); Assistant Professor, Waterloo + \item Sam Wiseman (2019); Assistant Professor, Duke University + \item Yoon Kim (2020); Assistant Professor, MIT + \item Sebastian Gehrmann (2020); Google NLP \end{itemize} -\ind Current Harvard Students - -\begin{itemize} -\item Yuntian Deng (Target 2022) -\item Jiawei Zhou (Target 2022) -\end{itemize} \ind Current Cornell Students \begin{itemize} -\item Justin Chiu (Target 2023) -\item Jack Morris (Admitted) -\item Woojeong Kim (Admitted) -\item Celine Lee (Admitted) -\end{itemize} - -\ind Former Undergraduate Students - -\begin{itemize} -\item Demi Guo (Stanford) -\item Lisa Li (Stanford) -\item Keyon Vafa (Columbia) -\item Rachit () - + \item Nathan Yan + \item Junxiong Wang + \item Jack Morris + \item Woojeong Kim + \item Celine Lee + \item Wenting Zhao \end{itemize} @@ -877,31 +906,32 @@ \ind Program Director 2020-; Computer Science Program, the largest Masters program at Cornell Tech. -\ind Admissions Committee 2020 +\ind Admissions Committee 2020-2024 \bigskip \marginhead{ {\vskip 0.3em}Teaching} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} -2021 & \ind Instructor, Topics in Machine Learning and NLP (10 students) , Cornell Tech, Spring. \\ -2020 & \ind Instructor, Topics in Machine Learning and NLP (100 students), Cornell Tech, Spring. \\ - & \ind Instructor, Machine Learning Engineering (100 students) (Rated 4.75/5), Cornell Tech, Fall. \\ - - 2019 & \ind Instructor, Machine Learning for NLP (50 students) , Harvard University, Spring. \\ - -2018 & \ind Instructor, Machine Learning for NLP (50 students) (Rated 4.8/5) , Harvard University, Spring. \\ -& \ind Instructor, Advanced Machine Learning (100 students), Harvard University, Fall. \\ -2017 & \ind Instructor, Machine Learning (250 students), Harvard University, Spring. \\ -& \ind Instructor, Advanced Machine Learning (100 students), Harvard University, Fall. \\ -2016 & \ind Instructor, Machine Learning for NLP (50 students) (Rated 4.9/5), Harvard University, Spring. \\ -2015 & \ind Instructor, Artificial Intelligence (100 students), Harvard University, Fall. \\ -2013 & \ind Instructor (with Michael Collins), Natural Language Processing, Columbia University, Fall. \\ -& \ind Head Teaching Assistant, Natural Language Processing , Michael Collins, Columbia University, Spring (taught on Coursera, 30,000+ registered students). \\ -2012 & \ind Head Teaching Assistant, Natural Language Processing, Michael Collins, Columbia University, Fall.\\ + 2020-2024 & \ind Instructor, Machine Learning Engineering (150 students) , Cornell Tech, Spring. \\ + 2021 & \ind Instructor, Topics in Machine Learning and NLP (10 students) , Cornell Tech, Spring. \\ + 2020 & \ind Instructor, Topics in Machine Learning and NLP (100 students), Cornell Tech, Spring. \\ + & \ind Instructor, Machine Learning Engineering (100 students) (Rated 4.75/5), Cornell Tech, Fall. \\ + + 2019 & \ind Instructor, Machine Learning for NLP (50 students) , Harvard University, Spring. \\ + + 2018 & \ind Instructor, Machine Learning for NLP (50 students) (Rated 4.8/5) , Harvard University, Spring. \\ + & \ind Instructor, Advanced Machine Learning (100 students), Harvard University, Fall. \\ + 2017 & \ind Instructor, Machine Learning (250 students), Harvard University, Spring. \\ + & \ind Instructor, Advanced Machine Learning (100 students), Harvard University, Fall. \\ + 2016 & \ind Instructor, Machine Learning for NLP (50 students) (Rated 4.9/5), Harvard University, Spring. \\ + 2015 & \ind Instructor, Artificial Intelligence (100 students), Harvard University, Fall. \\ + 2013 & \ind Instructor (with Michael Collins), Natural Language Processing, Columbia University, Fall. \\ + & \ind Head Teaching Assistant, Natural Language Processing , Michael Collins, Columbia University, Spring (taught on Coursera, 30,000+ registered students). \\ + 2012 & \ind Head Teaching Assistant, Natural Language Processing, Michael Collins, Columbia University, Fall. \\ \end{tabular} - \bigskip +\bigskip \marginhead{ {\vskip 0.3em}Patents} % \medskip @@ -928,112 +958,112 @@ \ind \href{ paper.link } { Llama2 Rust. } \begin{itemize} -\item llama2 in rust. + \item llama2 in rust. \end{itemize} \medskip \ind \href{ paper.link } { LLM Training Puzzles. } \begin{itemize} -\item puzzles for learning about distributed training. + \item puzzles for learning about distributed training. \end{itemize} \medskip \ind \href{ paper.link } { Thinking Like Transformers. } \begin{itemize} -\item learn to think like a transformers. + \item learn to think like a transformers. \end{itemize} \medskip \ind \href{ paper.link } { GPU-Puzzles. } \begin{itemize} -\item A series of puzzles for learning about the core aspects of modern deep learning coding. Includes puzzles for tensors, gpu's, and auto-differentiation.. + \item A series of puzzles for learning about the core aspects of modern deep learning coding. Includes puzzles for tensors, gpu's, and auto-differentiation.. \end{itemize} \medskip \ind \href{ paper.link } { Annotated S4. } \begin{itemize} -\item Annotated S4 is a pedagogical implementation of the S4 model for very long range sequnece modeling utilizing JAX as a method for explaining mathematically complex code.. + \item Annotated S4 is a pedagogical implementation of the S4 model for very long range sequnece modeling utilizing JAX as a method for explaining mathematically complex code.. \end{itemize} \medskip \ind \href{ paper.link } { PromptSource. } \begin{itemize} -\item PromptSource is an IDE for producing natural language prompts on real datasets. It was the basis of the T0 model for large-scale multitask training.. + \item PromptSource is an IDE for producing natural language prompts on real datasets. It was the basis of the T0 model for large-scale multitask training.. \end{itemize} \medskip \ind \href{ paper.link } { Break Through AI. } \begin{itemize} -\item Break Through AI is a free summer program for supporting female undergraduates to learn AI and ML skills in an applied environment. I teach an 8 week summer program on the core elements on ML in a coding first environment.. + \item Break Through AI is a free summer program for supporting female undergraduates to learn AI and ML skills in an applied environment. I teach an 8 week summer program on the core elements on ML in a coding first environment.. \end{itemize} \medskip \ind \href{ paper.link } { MiniConf. } \begin{itemize} -\item MiniConf is a project developed for ICLR as an easy-to-use tool for hosting fully remote asynchronous virtual conferences. It was heavily used in 2020 to host ACL, ICML, AKBC, AIStats, EMNLP, NeurIPS, and many other virtual conferences.. + \item MiniConf is a project developed for ICLR as an easy-to-use tool for hosting fully remote asynchronous virtual conferences. It was heavily used in 2020 to host ACL, ICML, AKBC, AIStats, EMNLP, NeurIPS, and many other virtual conferences.. \end{itemize} \medskip \ind \href{ paper.link } { MiniTorch. } \begin{itemize} -\item MiniTorch is a DIY teaching library to walkthrough the process of building a tensor, autodifferentiation library from scratch. It is used to teach machine learning engineering at Cornell Tech.. + \item MiniTorch is a DIY teaching library to walkthrough the process of building a tensor, autodifferentiation library from scratch. It is used to teach machine learning engineering at Cornell Tech.. \end{itemize} \medskip \ind \href{ paper.link } { Streambook. } \begin{itemize} -\item Streambook is a literate programming environment designed to make it easy to write publishable Jupyter notebooks without ever having to open a browser or break your github flow.. + \item Streambook is a literate programming environment designed to make it easy to write publishable Jupyter notebooks without ever having to open a browser or break your github flow.. \end{itemize} \medskip \ind \href{ paper.link } { Named Tensor Notation. } \begin{itemize} -\item Named Tensor Notation was a follow-up to the named tensor proposal to develop a mathematical notation for more explicit multi-dimensional dot products when describing neural network interactions.. + \item Named Tensor Notation was a follow-up to the named tensor proposal to develop a mathematical notation for more explicit multi-dimensional dot products when describing neural network interactions.. \end{itemize} \medskip \ind \href{ paper.link } { NLP Browser. } \begin{itemize} -\item NLP Browser is a web app that lets any easily browse through more than 150 datasets used in NLP and hosted by Hugging Face. The app is a pretty addictive way to casually learn about new datasets and challenges.. + \item NLP Browser is a web app that lets any easily browse through more than 150 datasets used in NLP and hosted by Hugging Face. The app is a pretty addictive way to casually learn about new datasets and challenges.. \end{itemize} \medskip \ind \href{ paper.link } { NamedTensor (Tensor Considered Harmful). } \begin{itemize} -\item Named Tensor is a proposal for adding a new datastructure to mathematical libraries to tread tensors more like dicts and less like tuples. This blog post had the impact of getting PyTorch to add a NamedTensor annotation in v1.3 of the libary.. + \item Named Tensor is a proposal for adding a new datastructure to mathematical libraries to tread tensors more like dicts and less like tuples. This blog post had the impact of getting PyTorch to add a NamedTensor annotation in v1.3 of the libary.. \end{itemize} \medskip \ind \href{ paper.link } { Torch Struct. } \begin{itemize} -\item Torch-Struct is a passion project of mine to test out whether deep learning libraries can be used to implement classical structured prediction. It includes heavily-tested reference reimplementations of many core NLP algorithms.. + \item Torch-Struct is a passion project of mine to test out whether deep learning libraries can be used to implement classical structured prediction. It includes heavily-tested reference reimplementations of many core NLP algorithms.. \end{itemize} \medskip \ind \href{ paper.link } { OpenNMT. } \begin{itemize} -\item A full service open-source neural machine translation system. Originally developed in Lua with Systran, since ported to PyTorch and TensorFlow and maintained externally.. + \item A full service open-source neural machine translation system. Originally developed in Lua with Systran, since ported to PyTorch and TensorFlow and maintained externally.. \end{itemize} \medskip \ind \href{ paper.link } { The Annotated Transformer. } \begin{itemize} -\item The annotated transformer was an experiment in blogging based on literate papers. The idea was to teach researchers how an important model in NLP works by aligning the paper line-by-line with an implementation. The blog post was widely distributed, and there have been many follow-ups for new model.. + \item The annotated transformer was an experiment in blogging based on literate papers. The idea was to teach researchers how an important model in NLP works by aligning the paper line-by-line with an implementation. The blog post was widely distributed, and there have been many follow-ups for new model.. \end{itemize} \medskip @@ -1158,7 +1188,7 @@ % - \bigskip +\bigskip %% Publications @@ -1185,8 +1215,8 @@ \medskip \ind Lead Engineer (Platform Team), {\sl Facebook}, 2007 -- 2009, Palo Alto, CA. \begin{itemize} -\item Developed compiler for Facebook Markup Language (FBML) to sanitize user content. -\item Developed system for crowd-sourced translation of Facebook user text. + \item Developed compiler for Facebook Markup Language (FBML) to sanitize user content. + \item Developed system for crowd-sourced translation of Facebook user text. \end{itemize} @@ -1208,140 +1238,144 @@ \marginhead{ {\vskip 0.4em}Invited Talks \newline} \medskip \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2023 - & \ind Panel, NeurIPS Keynote. \\ - & \ind Invited Talk, JHU. \\ - & \ind Invited Talk, NYU. \\ - & \ind Keynote Talk, MLSys 2023. \\ - & \ind Keynote Talk, Simon Workshop on LLMs . \\ - & \ind Invited Talk, Dagstuhl Seminar. \\ - & \ind Invited Talk, UCSD AI Seminar. \\ - & \ind Invited Talk, Penn NLP Seminar. \\ - & \ind Invited Talk, Stanford NLP Seminar. \\ - 2022 - & \ind Invited Talk, SoCal NLP. \\ - & \ind Invited Talk, LXMLS 2022. \\ - & \ind Invited Talk, MASC 2022. \\ - & \ind Invited Talk, Rutgers Efficient ML. \\ - & \ind Invited Talk, Georgia Tech NLP Seminar. \\ - & \ind Invited Talk, Pacific Research Lab NLP. \\ - 2021 - & \ind Invited Talk, NeurIPS Crowd Source ML. \\ - & \ind Invited Talk, NeurIPS AIPLANs Workshop. \\ - & \ind Invited Talk, Microsoft Efficient ML. \\ - & \ind Invited Talk, Stanford SysML. \\ - & \ind Invited Talk, Lisbon Machine Learning. \\ - & \ind Invited Talk, University of Cambridge. \\ - & \ind Invited Talk, Oracle. \\ - & \ind Invited Talk, UCSB. \\ - 2020 - & \ind Invited Talk, ByteDance. \\ - & \ind Invited Talk, Baidu. \\ - & \ind Colloquium, UMass Lowell. \\ - & \ind Invited Talk, London Machine Learning. \\ - & \ind Invited Talk, UCSB. \\ - & \ind Invited Talk, Baidu. \\ - & \ind Invited Talk, Google AI. \\ - & \ind Invited Talk, Oracle AI. \\ - & \ind Invited Talk, EMNLP Structured Prediction WS. \\ - & \ind Invited Talk, EMNLP SustaiNLP WS. \\ - \end{tabular} + 2024 + & \ind Panel, EMNLP Keynote. \\ + & \ind Richard Karp Lecture, Simons Institute. \\ + & \ind Keynote, IEEE Big Data. \\ + 2023 + & \ind Panel, NeurIPS Keynote. \\ + & \ind Invited Talk, JHU. \\ + & \ind Invited Talk, NYU. \\ + & \ind Keynote Talk, MLSys 2023. \\ + & \ind Keynote Talk, Simon Workshop on LLMs . \\ + & \ind Invited Talk, Dagstuhl Seminar. \\ + & \ind Invited Talk, UCSD AI Seminar. \\ + & \ind Invited Talk, Penn NLP Seminar. \\ + & \ind Invited Talk, Stanford NLP Seminar. \\ + 2022 + & \ind Invited Talk, SoCal NLP. \\ + & \ind Invited Talk, LXMLS 2022. \\ + & \ind Invited Talk, MASC 2022. \\ + & \ind Invited Talk, Rutgers Efficient ML. \\ + & \ind Invited Talk, Georgia Tech NLP Seminar. \\ + & \ind Invited Talk, Pacific Research Lab NLP. \\ + 2021 + & \ind Invited Talk, NeurIPS Crowd Source ML. \\ + & \ind Invited Talk, NeurIPS AIPLANs Workshop. \\ + & \ind Invited Talk, Microsoft Efficient ML. \\ + & \ind Invited Talk, Stanford SysML. \\ + & \ind Invited Talk, Lisbon Machine Learning. \\ + & \ind Invited Talk, University of Cambridge. \\ + & \ind Invited Talk, Oracle. \\ + & \ind Invited Talk, UCSB. \\ + 2020 + & \ind Invited Talk, ByteDance. \\ + & \ind Invited Talk, Baidu. \\ + & \ind Colloquium, UMass Lowell. \\ + & \ind Invited Talk, London Machine Learning. \\ + & \ind Invited Talk, UCSB. \\ + & \ind Invited Talk, Baidu. \\ + & \ind Invited Talk, Google AI. \\ + & \ind Invited Talk, Oracle AI. \\ + & \ind Invited Talk, EMNLP Structured Prediction WS. \\ + & \ind Invited Talk, EMNLP SustaiNLP WS. \\ +\end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2019 - & \ind Colloquium, University of Edinburgh, Spring.\\ - & \ind Colloquium, Tel Aviv University, Spring. \\ - & \ind Invited Talk, Conversational Intelligence Summer. \\ - & \ind Invited Talk, GANocracy, MIT, Summer. \\ - & \ind Invited Talk, OpenAI, MIT, Summer. \\ - & \ind Invited Talk, NeuralGen Workshop NAACL Summer. \\ - & \ind Invited Talk, Berkeley NLP, Fall.\\ - & \ind Keynote, PyTorch Developers Conference, Fall. \\ - \end{tabular} + 2019 + & \ind Colloquium, University of Edinburgh, Spring. \\ + & \ind Colloquium, Tel Aviv University, Spring. \\ + & \ind Invited Talk, Conversational Intelligence Summer. \\ + & \ind Invited Talk, GANocracy, MIT, Summer. \\ + & \ind Invited Talk, OpenAI, MIT, Summer. \\ + & \ind Invited Talk, NeuralGen Workshop NAACL Summer. \\ + & \ind Invited Talk, Berkeley NLP, Fall. \\ + & \ind Keynote, PyTorch Developers Conference, Fall. \\ +\end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2018 - & \ind Invited Talk, University of Washington, Spring. \\ - & \ind Invited Talk, Allen Institute for AI, Spring. \\ - & \ind Invited Talk, MSR, Spring. \\ - & \ind Keynote, American Machine Translation Association, Spring. \\ - & \ind Invited Talk, University of Texas, Spring. \\ - & \ind Invited Talk, University of Maryland, Spring. \\ - & \ind Invited Talk, Georgetown, Spring. \\ - & \ind Invited Talk, Lisbon ML Summer School, Summer. \\ - & \ind Invited Talk, Columbia University, Fall. \\ - & \ind Invited Talk, New York University - Text as Data, Fall. \\ - & \ind Tutorial, EMNLP, Fall. \\ - \end{tabular} + 2018 + & \ind Invited Talk, University of Washington, Spring. \\ + & \ind Invited Talk, Allen Institute for AI, Spring. \\ + & \ind Invited Talk, MSR, Spring. \\ + & \ind Keynote, American Machine Translation Association, Spring. \\ + & \ind Invited Talk, University of Texas, Spring. \\ + & \ind Invited Talk, University of Maryland, Spring. \\ + & \ind Invited Talk, Georgetown, Spring. \\ + & \ind Invited Talk, Lisbon ML Summer School, Summer. \\ + & \ind Invited Talk, Columbia University, Fall. \\ + & \ind Invited Talk, New York University - Text as Data, Fall. \\ + & \ind Tutorial, EMNLP, Fall. \\ +\end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} -2017 - & \ind Invited Talk, Google Faculty Day, Spring. \\ - & \ind Invited Talk, New England Machine Learning Day, Spring. \\ - & \ind Invited Talk, Google, Spring. \\ - & \ind Invited Talk, Berkeley CS, Spring. \\ - & \ind Invited Talk, Notre Dame, Spring. \\ - & \ind Colloquium, TTI-Chicago, Spring. \\ - & \ind Invited Talk, Apple, Siri Team, Spring. \\ - & \ind Colloquium, Samsung Global AI Forum, Fall. \\ - & \ind Invited Talk, AMD, Fall. \\ - \end{tabular} + 2017 + & \ind Invited Talk, Google Faculty Day, Spring. \\ + & \ind Invited Talk, New England Machine Learning Day, Spring. \\ + & \ind Invited Talk, Google, Spring. \\ + & \ind Invited Talk, Berkeley CS, Spring. \\ + & \ind Invited Talk, Notre Dame, Spring. \\ + & \ind Colloquium, TTI-Chicago, Spring. \\ + & \ind Invited Talk, Apple, Siri Team, Spring. \\ + & \ind Colloquium, Samsung Global AI Forum, Fall. \\ + & \ind Invited Talk, AMD, Fall. \\ +\end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2016 - & \ind Invited Talk, NYU, Fall. \\ - & \ind Invited Talk, BBN Research, Fall. \\ - & \ind Invited Talk, Bloomberg, Fall. \\ - & \ind Invited Talk (Speech Group), MIT, Fall. \\ - & \ind Invited Talk, IBM Research, Fall. \\ - & \ind Colloquium, CMU, Fall. \\ - & \ind Invited Talk, Stanford NLP, Summer. \\ - & \ind Invited Talk, Oracle Labs, Summer. \\ - & \ind Invited Talk, Twitter, Summer. \\ - & \ind Colloquium, John Hopkins University, Spring. \\ - & \ind Colloquium, Rakuten, Spring. \\ + 2016 + & \ind Invited Talk, NYU, Fall. \\ + & \ind Invited Talk, BBN Research, Fall. \\ + & \ind Invited Talk, Bloomberg, Fall. \\ + & \ind Invited Talk (Speech Group), MIT, Fall. \\ + & \ind Invited Talk, IBM Research, Fall. \\ + & \ind Colloquium, CMU, Fall. \\ + & \ind Invited Talk, Stanford NLP, Summer. \\ + & \ind Invited Talk, Oracle Labs, Summer. \\ + & \ind Invited Talk, Twitter, Summer. \\ + & \ind Colloquium, John Hopkins University, Spring. \\ + & \ind Colloquium, Rakuten, Spring. \\ \end{tabular} \begin{tabular}{lp{11.5cm}} - 2014 + 2014 - & \ind Colloquium, University of Washington, Spring. \\ + & \ind Colloquium, University of Washington, Spring. \\ - & \ind Colloquium, NYU, Spring. \\ + & \ind Colloquium, NYU, Spring. \\ - & \ind Colloquium, CMU, Spring. \\ + & \ind Colloquium, CMU, Spring. \\ - & \ind Colloquium, MIT, Spring. \\ + & \ind Colloquium, MIT, Spring. \\ - & \ind Colloquium, Harvard, Spring. \\ + & \ind Colloquium, Harvard, Spring. \\ - & \ind Colloquium, TTIC, Spring. \\ + & \ind Colloquium, TTIC, Spring. \\ - & \ind Colloquium, University of Maryland, Spring. \\ + & \ind Colloquium, University of Maryland, Spring. \\ \end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2013 - & \ind Invited Tutorial, UMBC, October. \\ + 2013 + & \ind Invited Tutorial, UMBC, October. \\ - & \ind Invited Talk, CS and Social Science Seminar, UMass Amherst, October. \\ + & \ind Invited Talk, CS and Social Science Seminar, UMass Amherst, October. \\ - & \ind Talk, NLP Seminar, Columbia University, October. \\ - & \ind Invited Talk, ML Seminar, UMass Amherst, October. \\ + & \ind Talk, NLP Seminar, Columbia University, October. \\ + & \ind Invited Talk, ML Seminar, UMass Amherst, October. \\ - & \ind Invited Talk, Johnson Research Labs, NY, August. \\ + & \ind Invited Talk, Johnson Research Labs, NY, August. \\ - & \ind Invited Talk, Society for Historians of American Foreign Relations, Arlington, June. \\ + & \ind Invited Talk, Society for Historians of American Foreign Relations, Arlington, June. \\ - & \ind Invited Talk, Columbia University, Spring. \\ + & \ind Invited Talk, Columbia University, Spring. \\ - & \ind Invited Talk, NLP Seminar, City University of New York, Spring. \\ - 2012 & \ind Invited Tutorial, Neural Information Processing Systems (NIPS), December. \\ - 2011 & \ind Invited Tutorial, Google Research, Mountain View, August. \\ - & \ind Tutorial. Association of Computational Linguistic (ACL), June. \\ - & \ind Invited Talk, ML Seminar, University of Massachusetts, Amherst, Spring. \\ - & \ind ML Tea, MIT, January. \\ - 2010 & \ind NLP Seminar, USC/ISI, Summer. \\ - 2006 & \ind Invited Talk, Computational Linguistics Seminar, University of Pennsylvania, November. \\ + & \ind Invited Talk, NLP Seminar, City University of New York, Spring. \\ + 2012 & \ind Invited Tutorial, Neural Information Processing Systems (NIPS), December. \\ + 2011 & \ind Invited Tutorial, Google Research, Mountain View, August. \\ + & \ind Tutorial. Association of Computational Linguistic (ACL), June. \\ + & \ind Invited Talk, ML Seminar, University of Massachusetts, Amherst, Spring. \\ + & \ind ML Tea, MIT, January. \\ + 2010 & \ind NLP Seminar, USC/ISI, Summer. \\ + 2006 & \ind Invited Talk, Computational Linguistics Seminar, University of Pennsylvania, November. \\ \end{tabular} %\end{revnumerate} diff --git a/cv/cv.tex b/cv/cv.tex index 360fb08..0bd8e14 100644 --- a/cv/cv.tex +++ b/cv/cv.tex @@ -150,7 +150,7 @@ %%% Address and contact block %%%------------------------------------------------------------------------ \begin{minipage}[t]{2.95in} - \flushright {\footnotesize \href{http://rush-nlp.com}{Cornell University} \\ Cornell Tech, \\ \vspace{-0.05in} New York, NY } + \flushright {\footnotesize \href{http://rush-nlp.com}{Cornell University} \\ Cornell Tech, \\ \vspace{-0.05in} New York, NY } \end{minipage} \hfill @@ -159,10 +159,10 @@ %\end{minipage} \hfill \begin{minipage}[t]{1.7in} - \flushright %\footnotesize Phone: \myphone \\ - {\scriptsize \texttt{\href{mailto:\myemail}{\myemail}}} \\ - {\scriptsize \texttt{\href{\myweb}{\myweb}}} \\ - {\scriptsize \texttt{\href{http://twitter.com/\myfax}{@\myfax}}} \\ + \flushright %\footnotesize Phone: \myphone \\ + {\scriptsize \texttt{\href{mailto:\myemail}{\myemail}}} \\ + {\scriptsize \texttt{\href{\myweb}{\myweb}}} \\ + {\scriptsize \texttt{\href{http://twitter.com/\myfax}{@\myfax}}} \\ \end{minipage} @@ -210,36 +210,36 @@ \marginhead{ {\vskip 0.4em} Awards} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} -2023 & Best Paper Runner-up - NeurIPS \\ - & Outstanding Paper - EMNLP \\ -2021 & Best Demo Paper - EMNLP \\ - & Outstanding Short Paper - NAACL \\ - & Sloan Fellowship\\ -2020 & Best Demo Paper (Runner-Up), ACL \\ -& Best Paper - DAC (Hardware) \\ -& Best Demo Paper - EMNLP \\ -2019 & NSF Career Award \\ -& Best Demo Paper - Nominee, ACL \\ -2018 & Senior Program Chair, ICLR \\ -& Best Paper - Runner-Up, VAST (Visualization) \\ -2017 & Best Demo - Runner-Up, ACL \\ - & Invitation IJCAI Early Research Spotlight \\ -& Best Paper - Runner-Up, EMNLP \\ -2015 & NIPS Deep Learning Symposium (Invited Paper) \\ -2012 & Best Paper Award, NAACL \\ -2010 & Best Paper Award, EMNLP \\ + 2023 & Best Paper Runner-up - NeurIPS \\ + & Outstanding Paper - EMNLP \\ + 2021 & Best Demo Paper - EMNLP \\ + & Outstanding Short Paper - NAACL \\ + & Sloan Fellowship \\ + 2020 & Best Demo Paper (Runner-Up), ACL \\ + & Best Paper - DAC (Hardware) \\ + & Best Demo Paper - EMNLP \\ + 2019 & NSF Career Award \\ + & Best Demo Paper - Nominee, ACL \\ + 2018 & Senior Program Chair, ICLR \\ + & Best Paper - Runner-Up, VAST (Visualization) \\ + 2017 & Best Demo - Runner-Up, ACL \\ + & Invitation IJCAI Early Research Spotlight \\ + & Best Paper - Runner-Up, EMNLP \\ + 2015 & NIPS Deep Learning Symposium (Invited Paper) \\ + 2012 & Best Paper Award, NAACL \\ + 2010 & Best Paper Award, EMNLP \\ \end{tabular} \marginhead{ {\vskip 0.4em} Grants} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} -2019 & NSF Career Award \\ -& Sony Faculty Awards \\ -2018& Google, Facebook, and Amazon AWS Faculty Awards \\ -2017 & Bloomberg and Intel AI Collaboration Faculty Awards \\ -2016 & Microsoft Azure and Samsung AI Award \\ -2015 & Google Faculty Award \\ + 2019 & NSF Career Award \\ + & Sony Faculty Awards \\ + 2018 & Google, Facebook, and Amazon AWS Faculty Awards \\ + 2017 & Bloomberg and Intel AI Collaboration Faculty Awards \\ + 2016 & Microsoft Azure and Samsung AI Award \\ + 2015 & Google Faculty Award \\ \end{tabular} \pagebreak @@ -319,6 +319,9 @@ \bigskip +\ind President / Founder : +\ind COLM 2024- + \ind Secretary: \ind ICLR Board 2021-2024 @@ -346,38 +349,27 @@ \ind PhD Students -\ind Graduated Harvard Students +\ind Graduated Students \begin{itemize} -\item Sam Wiseman (2019); Assistant Professor, Duke University -\item Yoon Kim (2020); Assistant Professor, MIT -\item Sebastian Gehrmann (2020); Google NLP + \item Justin Chiu (2024); Cohere AI + \item Jiawei Zhou (2023); Assistant Professor, Stonybrook + \item Yuntian Deng (2023); Assistant Professor, Waterloo + \item Sam Wiseman (2019); Assistant Professor, Duke University + \item Yoon Kim (2020); Assistant Professor, MIT + \item Sebastian Gehrmann (2020); Google NLP \end{itemize} -\ind Current Harvard Students - -\begin{itemize} -\item Yuntian Deng (Target 2022) -\item Jiawei Zhou (Target 2022) -\end{itemize} \ind Current Cornell Students \begin{itemize} -\item Justin Chiu (Target 2023) -\item Jack Morris (Admitted) -\item Woojeong Kim (Admitted) -\item Celine Lee (Admitted) -\end{itemize} - -\ind Former Undergraduate Students - -\begin{itemize} -\item Demi Guo (Stanford) -\item Lisa Li (Stanford) -\item Keyon Vafa (Columbia) -\item Rachit () - + \item Nathan Yan + \item Junxiong Wang + \item Jack Morris + \item Woojeong Kim + \item Celine Lee + \item Wenting Zhao \end{itemize} @@ -386,31 +378,32 @@ \ind Program Director 2020-; Computer Science Program, the largest Masters program at Cornell Tech. -\ind Admissions Committee 2020 +\ind Admissions Committee 2020-2024 \bigskip \marginhead{ {\vskip 0.3em}Teaching} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} -2021 & \ind Instructor, Topics in Machine Learning and NLP (10 students) , Cornell Tech, Spring. \\ -2020 & \ind Instructor, Topics in Machine Learning and NLP (100 students), Cornell Tech, Spring. \\ - & \ind Instructor, Machine Learning Engineering (100 students) (Rated 4.75/5), Cornell Tech, Fall. \\ - - 2019 & \ind Instructor, Machine Learning for NLP (50 students) , Harvard University, Spring. \\ - -2018 & \ind Instructor, Machine Learning for NLP (50 students) (Rated 4.8/5) , Harvard University, Spring. \\ -& \ind Instructor, Advanced Machine Learning (100 students), Harvard University, Fall. \\ -2017 & \ind Instructor, Machine Learning (250 students), Harvard University, Spring. \\ -& \ind Instructor, Advanced Machine Learning (100 students), Harvard University, Fall. \\ -2016 & \ind Instructor, Machine Learning for NLP (50 students) (Rated 4.9/5), Harvard University, Spring. \\ -2015 & \ind Instructor, Artificial Intelligence (100 students), Harvard University, Fall. \\ -2013 & \ind Instructor (with Michael Collins), Natural Language Processing, Columbia University, Fall. \\ -& \ind Head Teaching Assistant, Natural Language Processing , Michael Collins, Columbia University, Spring (taught on Coursera, 30,000+ registered students). \\ -2012 & \ind Head Teaching Assistant, Natural Language Processing, Michael Collins, Columbia University, Fall.\\ + 2020-2024 & \ind Instructor, Machine Learning Engineering (150 students) , Cornell Tech, Spring. \\ + 2021 & \ind Instructor, Topics in Machine Learning and NLP (10 students) , Cornell Tech, Spring. \\ + 2020 & \ind Instructor, Topics in Machine Learning and NLP (100 students), Cornell Tech, Spring. \\ + & \ind Instructor, Machine Learning Engineering (100 students) (Rated 4.75/5), Cornell Tech, Fall. \\ + + 2019 & \ind Instructor, Machine Learning for NLP (50 students) , Harvard University, Spring. \\ + + 2018 & \ind Instructor, Machine Learning for NLP (50 students) (Rated 4.8/5) , Harvard University, Spring. \\ + & \ind Instructor, Advanced Machine Learning (100 students), Harvard University, Fall. \\ + 2017 & \ind Instructor, Machine Learning (250 students), Harvard University, Spring. \\ + & \ind Instructor, Advanced Machine Learning (100 students), Harvard University, Fall. \\ + 2016 & \ind Instructor, Machine Learning for NLP (50 students) (Rated 4.9/5), Harvard University, Spring. \\ + 2015 & \ind Instructor, Artificial Intelligence (100 students), Harvard University, Fall. \\ + 2013 & \ind Instructor (with Michael Collins), Natural Language Processing, Columbia University, Fall. \\ + & \ind Head Teaching Assistant, Natural Language Processing , Michael Collins, Columbia University, Spring (taught on Coursera, 30,000+ registered students). \\ + 2012 & \ind Head Teaching Assistant, Natural Language Processing, Michael Collins, Columbia University, Fall. \\ \end{tabular} - \bigskip +\bigskip \marginhead{ {\vskip 0.3em}Patents} % \medskip @@ -437,7 +430,7 @@ {% for paper in projects %} \ind \href{ paper.link } { {{paper.title}}. } \begin{itemize} -\item {{paper.abstract}}. + \item {{paper.abstract}}. \end{itemize} \medskip @@ -482,7 +475,7 @@ % {% endif %} {% endfor %} - \bigskip +\bigskip %% Publications @@ -509,8 +502,8 @@ \medskip \ind Lead Engineer (Platform Team), {\sl Facebook}, 2007 -- 2009, Palo Alto, CA. \begin{itemize} -\item Developed compiler for Facebook Markup Language (FBML) to sanitize user content. -\item Developed system for crowd-sourced translation of Facebook user text. + \item Developed compiler for Facebook Markup Language (FBML) to sanitize user content. + \item Developed system for crowd-sourced translation of Facebook user text. \end{itemize} @@ -532,140 +525,144 @@ \marginhead{ {\vskip 0.4em}Invited Talks \newline} \medskip \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2023 - & \ind Panel, NeurIPS Keynote. \\ - & \ind Invited Talk, JHU. \\ - & \ind Invited Talk, NYU. \\ - & \ind Keynote Talk, MLSys 2023. \\ - & \ind Keynote Talk, Simon Workshop on LLMs . \\ - & \ind Invited Talk, Dagstuhl Seminar. \\ - & \ind Invited Talk, UCSD AI Seminar. \\ - & \ind Invited Talk, Penn NLP Seminar. \\ - & \ind Invited Talk, Stanford NLP Seminar. \\ - 2022 - & \ind Invited Talk, SoCal NLP. \\ - & \ind Invited Talk, LXMLS 2022. \\ - & \ind Invited Talk, MASC 2022. \\ - & \ind Invited Talk, Rutgers Efficient ML. \\ - & \ind Invited Talk, Georgia Tech NLP Seminar. \\ - & \ind Invited Talk, Pacific Research Lab NLP. \\ - 2021 - & \ind Invited Talk, NeurIPS Crowd Source ML. \\ - & \ind Invited Talk, NeurIPS AIPLANs Workshop. \\ - & \ind Invited Talk, Microsoft Efficient ML. \\ - & \ind Invited Talk, Stanford SysML. \\ - & \ind Invited Talk, Lisbon Machine Learning. \\ - & \ind Invited Talk, University of Cambridge. \\ - & \ind Invited Talk, Oracle. \\ - & \ind Invited Talk, UCSB. \\ - 2020 - & \ind Invited Talk, ByteDance. \\ - & \ind Invited Talk, Baidu. \\ - & \ind Colloquium, UMass Lowell. \\ - & \ind Invited Talk, London Machine Learning. \\ - & \ind Invited Talk, UCSB. \\ - & \ind Invited Talk, Baidu. \\ - & \ind Invited Talk, Google AI. \\ - & \ind Invited Talk, Oracle AI. \\ - & \ind Invited Talk, EMNLP Structured Prediction WS. \\ - & \ind Invited Talk, EMNLP SustaiNLP WS. \\ - \end{tabular} + 2024 + & \ind Panel, EMNLP Keynote. \\ + & \ind Richard Karp Lecture, Simons Institute. \\ + & \ind Keynote, IEEE Big Data. \\ + 2023 + & \ind Panel, NeurIPS Keynote. \\ + & \ind Invited Talk, JHU. \\ + & \ind Invited Talk, NYU. \\ + & \ind Keynote Talk, MLSys 2023. \\ + & \ind Keynote Talk, Simon Workshop on LLMs . \\ + & \ind Invited Talk, Dagstuhl Seminar. \\ + & \ind Invited Talk, UCSD AI Seminar. \\ + & \ind Invited Talk, Penn NLP Seminar. \\ + & \ind Invited Talk, Stanford NLP Seminar. \\ + 2022 + & \ind Invited Talk, SoCal NLP. \\ + & \ind Invited Talk, LXMLS 2022. \\ + & \ind Invited Talk, MASC 2022. \\ + & \ind Invited Talk, Rutgers Efficient ML. \\ + & \ind Invited Talk, Georgia Tech NLP Seminar. \\ + & \ind Invited Talk, Pacific Research Lab NLP. \\ + 2021 + & \ind Invited Talk, NeurIPS Crowd Source ML. \\ + & \ind Invited Talk, NeurIPS AIPLANs Workshop. \\ + & \ind Invited Talk, Microsoft Efficient ML. \\ + & \ind Invited Talk, Stanford SysML. \\ + & \ind Invited Talk, Lisbon Machine Learning. \\ + & \ind Invited Talk, University of Cambridge. \\ + & \ind Invited Talk, Oracle. \\ + & \ind Invited Talk, UCSB. \\ + 2020 + & \ind Invited Talk, ByteDance. \\ + & \ind Invited Talk, Baidu. \\ + & \ind Colloquium, UMass Lowell. \\ + & \ind Invited Talk, London Machine Learning. \\ + & \ind Invited Talk, UCSB. \\ + & \ind Invited Talk, Baidu. \\ + & \ind Invited Talk, Google AI. \\ + & \ind Invited Talk, Oracle AI. \\ + & \ind Invited Talk, EMNLP Structured Prediction WS. \\ + & \ind Invited Talk, EMNLP SustaiNLP WS. \\ +\end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2019 - & \ind Colloquium, University of Edinburgh, Spring.\\ - & \ind Colloquium, Tel Aviv University, Spring. \\ - & \ind Invited Talk, Conversational Intelligence Summer. \\ - & \ind Invited Talk, GANocracy, MIT, Summer. \\ - & \ind Invited Talk, OpenAI, MIT, Summer. \\ - & \ind Invited Talk, NeuralGen Workshop NAACL Summer. \\ - & \ind Invited Talk, Berkeley NLP, Fall.\\ - & \ind Keynote, PyTorch Developers Conference, Fall. \\ - \end{tabular} + 2019 + & \ind Colloquium, University of Edinburgh, Spring. \\ + & \ind Colloquium, Tel Aviv University, Spring. \\ + & \ind Invited Talk, Conversational Intelligence Summer. \\ + & \ind Invited Talk, GANocracy, MIT, Summer. \\ + & \ind Invited Talk, OpenAI, MIT, Summer. \\ + & \ind Invited Talk, NeuralGen Workshop NAACL Summer. \\ + & \ind Invited Talk, Berkeley NLP, Fall. \\ + & \ind Keynote, PyTorch Developers Conference, Fall. \\ +\end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2018 - & \ind Invited Talk, University of Washington, Spring. \\ - & \ind Invited Talk, Allen Institute for AI, Spring. \\ - & \ind Invited Talk, MSR, Spring. \\ - & \ind Keynote, American Machine Translation Association, Spring. \\ - & \ind Invited Talk, University of Texas, Spring. \\ - & \ind Invited Talk, University of Maryland, Spring. \\ - & \ind Invited Talk, Georgetown, Spring. \\ - & \ind Invited Talk, Lisbon ML Summer School, Summer. \\ - & \ind Invited Talk, Columbia University, Fall. \\ - & \ind Invited Talk, New York University - Text as Data, Fall. \\ - & \ind Tutorial, EMNLP, Fall. \\ - \end{tabular} + 2018 + & \ind Invited Talk, University of Washington, Spring. \\ + & \ind Invited Talk, Allen Institute for AI, Spring. \\ + & \ind Invited Talk, MSR, Spring. \\ + & \ind Keynote, American Machine Translation Association, Spring. \\ + & \ind Invited Talk, University of Texas, Spring. \\ + & \ind Invited Talk, University of Maryland, Spring. \\ + & \ind Invited Talk, Georgetown, Spring. \\ + & \ind Invited Talk, Lisbon ML Summer School, Summer. \\ + & \ind Invited Talk, Columbia University, Fall. \\ + & \ind Invited Talk, New York University - Text as Data, Fall. \\ + & \ind Tutorial, EMNLP, Fall. \\ +\end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} -2017 - & \ind Invited Talk, Google Faculty Day, Spring. \\ - & \ind Invited Talk, New England Machine Learning Day, Spring. \\ - & \ind Invited Talk, Google, Spring. \\ - & \ind Invited Talk, Berkeley CS, Spring. \\ - & \ind Invited Talk, Notre Dame, Spring. \\ - & \ind Colloquium, TTI-Chicago, Spring. \\ - & \ind Invited Talk, Apple, Siri Team, Spring. \\ - & \ind Colloquium, Samsung Global AI Forum, Fall. \\ - & \ind Invited Talk, AMD, Fall. \\ - \end{tabular} + 2017 + & \ind Invited Talk, Google Faculty Day, Spring. \\ + & \ind Invited Talk, New England Machine Learning Day, Spring. \\ + & \ind Invited Talk, Google, Spring. \\ + & \ind Invited Talk, Berkeley CS, Spring. \\ + & \ind Invited Talk, Notre Dame, Spring. \\ + & \ind Colloquium, TTI-Chicago, Spring. \\ + & \ind Invited Talk, Apple, Siri Team, Spring. \\ + & \ind Colloquium, Samsung Global AI Forum, Fall. \\ + & \ind Invited Talk, AMD, Fall. \\ +\end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2016 - & \ind Invited Talk, NYU, Fall. \\ - & \ind Invited Talk, BBN Research, Fall. \\ - & \ind Invited Talk, Bloomberg, Fall. \\ - & \ind Invited Talk (Speech Group), MIT, Fall. \\ - & \ind Invited Talk, IBM Research, Fall. \\ - & \ind Colloquium, CMU, Fall. \\ - & \ind Invited Talk, Stanford NLP, Summer. \\ - & \ind Invited Talk, Oracle Labs, Summer. \\ - & \ind Invited Talk, Twitter, Summer. \\ - & \ind Colloquium, John Hopkins University, Spring. \\ - & \ind Colloquium, Rakuten, Spring. \\ + 2016 + & \ind Invited Talk, NYU, Fall. \\ + & \ind Invited Talk, BBN Research, Fall. \\ + & \ind Invited Talk, Bloomberg, Fall. \\ + & \ind Invited Talk (Speech Group), MIT, Fall. \\ + & \ind Invited Talk, IBM Research, Fall. \\ + & \ind Colloquium, CMU, Fall. \\ + & \ind Invited Talk, Stanford NLP, Summer. \\ + & \ind Invited Talk, Oracle Labs, Summer. \\ + & \ind Invited Talk, Twitter, Summer. \\ + & \ind Colloquium, John Hopkins University, Spring. \\ + & \ind Colloquium, Rakuten, Spring. \\ \end{tabular} \begin{tabular}{lp{11.5cm}} - 2014 + 2014 - & \ind Colloquium, University of Washington, Spring. \\ + & \ind Colloquium, University of Washington, Spring. \\ - & \ind Colloquium, NYU, Spring. \\ + & \ind Colloquium, NYU, Spring. \\ - & \ind Colloquium, CMU, Spring. \\ + & \ind Colloquium, CMU, Spring. \\ - & \ind Colloquium, MIT, Spring. \\ + & \ind Colloquium, MIT, Spring. \\ - & \ind Colloquium, Harvard, Spring. \\ + & \ind Colloquium, Harvard, Spring. \\ - & \ind Colloquium, TTIC, Spring. \\ + & \ind Colloquium, TTIC, Spring. \\ - & \ind Colloquium, University of Maryland, Spring. \\ + & \ind Colloquium, University of Maryland, Spring. \\ \end{tabular} \hspace{-1cm} \begin{tabular}{lp{11.5cm}} - 2013 - & \ind Invited Tutorial, UMBC, October. \\ + 2013 + & \ind Invited Tutorial, UMBC, October. \\ - & \ind Invited Talk, CS and Social Science Seminar, UMass Amherst, October. \\ + & \ind Invited Talk, CS and Social Science Seminar, UMass Amherst, October. \\ - & \ind Talk, NLP Seminar, Columbia University, October. \\ - & \ind Invited Talk, ML Seminar, UMass Amherst, October. \\ + & \ind Talk, NLP Seminar, Columbia University, October. \\ + & \ind Invited Talk, ML Seminar, UMass Amherst, October. \\ - & \ind Invited Talk, Johnson Research Labs, NY, August. \\ + & \ind Invited Talk, Johnson Research Labs, NY, August. \\ - & \ind Invited Talk, Society for Historians of American Foreign Relations, Arlington, June. \\ + & \ind Invited Talk, Society for Historians of American Foreign Relations, Arlington, June. \\ - & \ind Invited Talk, Columbia University, Spring. \\ + & \ind Invited Talk, Columbia University, Spring. \\ - & \ind Invited Talk, NLP Seminar, City University of New York, Spring. \\ - 2012 & \ind Invited Tutorial, Neural Information Processing Systems (NIPS), December. \\ - 2011 & \ind Invited Tutorial, Google Research, Mountain View, August. \\ - & \ind Tutorial. Association of Computational Linguistic (ACL), June. \\ - & \ind Invited Talk, ML Seminar, University of Massachusetts, Amherst, Spring. \\ - & \ind ML Tea, MIT, January. \\ - 2010 & \ind NLP Seminar, USC/ISI, Summer. \\ - 2006 & \ind Invited Talk, Computational Linguistics Seminar, University of Pennsylvania, November. \\ + & \ind Invited Talk, NLP Seminar, City University of New York, Spring. \\ + 2012 & \ind Invited Tutorial, Neural Information Processing Systems (NIPS), December. \\ + 2011 & \ind Invited Tutorial, Google Research, Mountain View, August. \\ + & \ind Tutorial. Association of Computational Linguistic (ACL), June. \\ + & \ind Invited Talk, ML Seminar, University of Massachusetts, Amherst, Spring. \\ + & \ind ML Tea, MIT, January. \\ + 2010 & \ind NLP Seminar, USC/ISI, Summer. \\ + 2006 & \ind Invited Talk, Computational Linguistics Seminar, University of Pennsylvania, November. \\ \end{tabular} %\end{revnumerate} diff --git a/cv/make.sh b/cv/make.sh index cd8c9bb..c6083f2 100644 --- a/cv/make.sh +++ b/cv/make.sh @@ -1,7 +1,7 @@ cat ../_data/papers.yaml ../_data/extra.yaml ../_data/code.yaml ../_data/projects.yaml > /tmp/all.yaml -jinja2 cv.tex /tmp/all.yaml --format yaml > cv.comp.tex +uvx --with jinja2-cli --with pyyaml jinja2 cv.tex /tmp/all.yaml --format yaml > cv.comp.tex pdflatex cv.comp.tex -jinja2 cv_short.tex /tmp/all.yaml --format yaml > cv_short.comp.tex +uvx --with jinja2-cli --with pyyaml jinja2 cv_short.tex /tmp/all.yaml --format yaml > cv_short.comp.tex pdflatex cv_short.comp.tex -jinja2 cv_tenure.tex /tmp/all.yaml --format yaml > cv_tenure.comp.tex +uvx --with jinja2-cli --with pyyaml jinja2 cv_tenure.tex /tmp/all.yaml --format yaml > cv_tenure.comp.tex pdflatex cv_tenure.comp.tex diff --git a/index.html b/index.html index 43fa409..528cdf8 100644 --- a/index.html +++ b/index.html @@ -27,21 +27,21 @@

Alexander Rush

- - My research aims to build and improve - generative AI. We are interested primarily in tasks that involve - text generation, historically translation, summarization, and - data-to-text generation. Methodologically, we study - data-driven probabilistic methods that combine deep-learning + My research group aims to build and improve + language models. Methodologically, we study + data-driven methods that combine deep-learning based models with probabilistic controls. + We are interested in applications in improved scaling, + efficiency, model reasoning, and long-context generation.

- I am also interested in open-source NLP and deep learning, and - develop projects to make deep learning systems safer, more clear, and easier to + I am also interested in open-source deep learning LLMs, and + develop projects to make systems safer, more clear, and easier to use. I work part-time at Hugging Face and like to release various software projects to support NLP and DL research. + I host a YouTube channel with technical talks about topics I am interested in.

@@ -65,7 +65,7 @@

Recognition

Selected Papers

-A selection of papers from the last several years that represent my research interests and style. +A selection of papers that represent my research interests and style.

@@ -103,7 +103,7 @@

Contact


- - - diff --git a/papers.html b/papers.html index 5e1ef43..124e357 100644 --- a/papers.html +++ b/papers.html @@ -8,142 +8,292 @@

Papers

- -

- - -My full list of papers is here. + My full list of papers is + here.

-{% for paper in site.data.papers.papers %} - - - -{% endfor %} + {% for paper in site.data.papers.papers %} + + + + + + + {% endfor %}
- {% if paper.image %} - - {% else %} - - {% endif %} - - -{{paper.title}} -
-{{paper.authors}}.
-{{paper.conference}}
- -
- -
+ {{paper.title}}
+ {{paper.authors}}.
+ {{paper.conference}}
+ +
+
-

PhD Publications

+

PhD Publications

- -A Constrained Viterbi Relaxation for Bidirectional Word Alignment. -
-Yin-Wen Chang, -Alexander M. Rush, -John DeNero, and -Michael Collins.
-Proceedings of ACL 2014.
pdf slides + + A Constrained Viterbi Relaxation for Bidirectional Word Alignment.
+ Yin-Wen Chang, + Alexander M. Rush, John DeNero, and + Michael Collins.
+ Proceedings of ACL 2014.
pdf + slides
-
- -Optimal Beam Search for Machine Translation -
-Alexander M. Rush, -Yin-Wen Chang, and -Michael Collins.
-Proceedings of EMNLP 2013.
pdf slides + + Optimal Beam Search for Machine Translation
+ Alexander M. Rush, + Yin-Wen Chang, and + Michael Collins.
+ Proceedings of EMNLP 2013.
pdf + slides
-Spectral Learning of Refinement HMMs.
- Karl Stratos, -Alexander M. Rush, - Shay B. Cohen, -and Michael Collins. -
-Proceedings of CoNLL 2013.
pdf   + Spectral Learning of Refinement HMMs.
+ + Karl Stratos, + Alexander M. Rush, + Shay B. Cohen, and + Michael Collins. +
+ Proceedings of CoNLL 2013.
+ pdf +  
- -Improved Parsing and POS Tagging Using Inter-Sentence Consistency Constraints -
-Alexander M. Rush, -Roi Reichert, -Michael Collins, and -Amir Globerson.
-Proceedings of EMNLP 2012.
pdf   + + Improved Parsing and POS Tagging Using Inter-Sentence Consistency + Constraints
+ Alexander M. Rush, Roi Reichert, + Michael Collins, and + Amir Globerson.
+ Proceedings of EMNLP 2012.
+ pdf  
- -Vine Pruning for Efficient Multi-Pass Dependency Parsing.
-Alexander M. Rush -and Slav Petrov.
-Proceedings of NAACL 2012.
Best Paper Award
pdf slides + + Vine Pruning for Efficient Multi-Pass Dependency Parsing.
+ Alexander M. Rush + and Slav Petrov.
+ Proceedings of NAACL 2012.
+ Best Paper Award
+ pdf + slides
-
- A Tutorial on Dual Decomposition and Lagrangian Relaxation for Inference in Natural Language Processing.
-Alexander M. Rush and -Michael Collins.
-Tutorial at NIPS 2011. slides -Tutorial at ACL 2011. slides - - pdf - + + A Tutorial on Dual Decomposition and Lagrangian Relaxation for Inference + in Natural Language Processing.
+ Alexander M. Rush + and + Michael Collins.
+ Tutorial at NIPS 2011. + slides + Tutorial at ACL 2011. + slides + + pdf
-Exact Decoding of Syntactic Translation Models through Lagrangian Relaxation.
-Alexander M. Rush and -Michael Collins.
-Proceedings of ACL 2011.
pdf slides + Exact Decoding of Syntactic Translation Models through Lagrangian + Relaxation.
+ Alexander M. Rush + and + Michael Collins.
+ Proceedings of ACL 2011.
pdf + + slides
-
-Dual Decomposition for Parsing with Non-Projective Head Automata.
-Terry Koo, -Alexander M. Rush, -Michael Collins, -Tommi Jaakkola, -and David Sontag.
-Proceedings of EMNLP 2010.
Best Paper Award
pdf slides + Dual Decomposition for Parsing with Non-Projective Head Automata.
+ Terry Koo, + Alexander M. Rush, + Michael Collins, + Tommi Jaakkola, and + David Sontag.
+ Proceedings of EMNLP 2010.
+ Best Paper Award
+ pdf + slides
- -On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing.
-Alexander M. Rush, -David Sontag, -Michael Collins, -and Tommi Jaakkola
-Proceedings of EMNLP 2010.
pdf slides + + On Dual Decomposition and Linear Programming Relaxations for Natural + Language Processing.
+ Alexander M. Rush, + David Sontag, + Michael Collins, and + Tommi Jaakkola
+ Proceedings of EMNLP 2010.
+ pdf + slides
-Induction of probabilistic synchronous tree-insertion grammars for machine translation.
-Rebecca Nesson, -Stuart M. Shieber, -and Alexander M. Rush.
-Proceedings of AMTA 2006. -
pdf   + Induction of probabilistic synchronous tree-insertion grammars for + machine translation.
+ Rebecca Nesson, + Stuart M. Shieber, and + Alexander M. Rush.
+ Proceedings of AMTA 2006. +
+ pdf +  
-Dissertation: Lagrangian Relaxation for Natural Language Decoding.
-Alexander M. Rush.
-MIT CSAIL (advisor Michael Collins). -
pdf job talk + Dissertation: Lagrangian Relaxation for Natural Language Decoding.
+ Alexander M. Rush.
+ MIT CSAIL (advisor + Michael Collins).
+ pdf + job talk
-