@@ -37,6 +37,7 @@ We welcome you to join us (via issues, PRs, [Slack](https://join.slack.com/t/dat
----
## News
+-  [2024-08-09] We propose Img-Diff, which enhances the performance of multimodal large language models through *contrastive data synthesis*, achieving a score that is 12 points higher than GPT-4V on the [MMVP benchmark](https://tsb0601.github.io/mmvp_blog/). See more details in our [paper](https://arxiv.org/abs/2408.04594), and download the dataset from [huggingface](https://huggingface.co/datasets/datajuicer/Img-Diff) and [modelscope](https://modelscope.cn/datasets/Data-Juicer/Img-Diff).
-  [2024-07-24] "Tianchi Better Synth Data Synthesis Competition for Multimodal Large Models" — Our 4th data-centric LLM competition has kicked off! Please visit the competition's [official website](https://tianchi.aliyun.com/competition/entrance/532251) for more information.
-  [2024-07-17] We utilized the Data-Juicer [Sandbox Laboratory Suite](https://github.com/modelscope/data-juicer/blob/main/docs/Sandbox.md) to systematically optimize data and models through an co-development workflow between data and models, achieving a new top spot on the [VBench](https://huggingface.co/spaces/Vchitect/VBench_Leaderboard) text-to-video leaderboard. The related achievements have been compiled and published in a [paper](http://arxiv.org/abs/2407.11784), and the model has been released on the [ModelScope](https://modelscope.cn/models/Data-Juicer/Data-Juicer-T2V) and [HuggingFace](https://huggingface.co/datajuicer/Data-Juicer-T2V) platforms.
-  [2024-07-12] Our *awesome list of MLLM-Data* has evolved into a systemic [survey](https://arxiv.org/abs/2407.08583) from model-data co-development perspective. Welcome to [explore](docs/awesome_llm_data.md) and contribute!
@@ -450,6 +451,8 @@ If you find our work useful for your research or development, please kindly cite
- [The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective](https://arxiv.org/abs/2407.08583)
+- [ImgDiff: Contrastive Data Synthesis for Vision Large Language Models](https://arxiv.org/abs/2408.04594)
+
- [Data Mixing Made Efficient: A Bivariate Scaling Law for Language Model Pretraining](https://arxiv.org/abs/2402.11505)
diff --git a/README_ZH.md b/README_ZH.md
index 473b560e8..571b4545d 100644
--- a/README_ZH.md
+++ b/README_ZH.md
@@ -31,6 +31,7 @@ Data-Juicer正在积极更新和维护中，我们将定期强化和新增更多
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## 新消息
+-  [2024-08-09] 我们提出了Img-Diff，它通过*对比数据合成*来增强多模态大型语言模型的性能，在[MMVP benchmark](https://tsb0601.github.io/mmvp_blog/)中比GPT-4V高出12个点。 更多细节请参阅我们的 [论文](https://arxiv.org/abs/2408.04594), 以及从 [huggingface](https://huggingface.co/datasets/datajuicer/Img-Diff) 和 [modelscope](https://modelscope.cn/datasets/Data-Juicer/Img-Diff)下载这份数据集。
-  [2024-07-24] “天池 Better Synth 多模态大模型数据合成赛”——第四届Data-Juicer大模型数据挑战赛已经正式启动！立即访问[竞赛官网](https://tianchi.aliyun.com/competition/entrance/532251)，了解赛事详情。
- [2024-07-17] 我们利用Data-Juicer[沙盒实验室套件](https://github.com/modelscope/data-juicer/blob/main/docs/Sandbox-ZH.md)，通过数据与模型间的系统性研发工作流，调优数据和模型，在[VBench](https://huggingface.co/spaces/Vchitect/VBench_Leaderboard)文生视频排行榜取得了新的榜首。相关成果已经整理发表在[论文](http://arxiv.org/abs/2407.11784)中，并且模型已在[ModelScope](https://modelscope.cn/models/Data-Juicer/Data-Juicer-T2V)和[HuggingFace](https://huggingface.co/datajuicer/Data-Juicer-T2V)平台发布。
- [2024-07-12] 我们的MLLM-Data精选列表已经演化为一个模型-数据协同开发的角度系统性[综述](https://arxiv.org/abs/2407.08583)。欢迎[浏览](docs/awesome_llm_data.md)或参与贡献!
@@ -423,6 +424,8 @@ Data-Juicer 感谢并参考了社区开源项目：
- [The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective](https://arxiv.org/abs/2407.08583)
+- [ImgDiff: Contrastive Data Synthesis for Vision Large Language Models](https://arxiv.org/abs/2408.04594)
+
- [Data Mixing Made Efficient: A Bivariate Scaling Law for Language Model Pretraining](https://arxiv.org/abs/2402.11505)
diff --git a/docs/sphinx_doc/source/_static/tutorial_kdd24.html b/docs/sphinx_doc/source/_static/tutorial_kdd24.html
index 3d5a6755d..4805aaa82 100644
--- a/docs/sphinx_doc/source/_static/tutorial_kdd24.html
+++ b/docs/sphinx_doc/source/_static/tutorial_kdd24.html
@@ -115,6 +115,8 @@ tutorial jupyter nootbooks + (pdf)
@@ -152,7 +154,7 @@