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 title: LLM-based FAQ Rewrites
-summary: "**Enhancing Editorial Tasks: A Case Study on Rewriting Customer Help Page Contents Using Large Language Models**<br><br>
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+summary: "**Enhancing Editorial Tasks: A Case Study on Rewriting Customer Help Page Contents Using Large Language Models**<br>
 We introduce a German-language dataset comprising Frequently Asked Question-Answer pairs: raw FAQ drafts, their revisions by professional editors and LLM generated revisions. The data was used to investigate the use of large language models (LLMs) to enhance the editorial process of rewriting customer help pages. The corpus comprises 56 question-answer pairs addressing potential customer inquiries across various topics. For each FAQ pair, a raw input is provided by specialized departments, and a rewritten gold output is crafted by a professional editor of Deutsche Telekom. The final dataset also includes LLM generated FAQ-pairs.
 Please see our [paper](https://aclanthology.org/2024.inlg-main.13/) accepted at INLG 20204, Tokyo, Japan. You can find the Github repo containing the dataset here [https://github.com/DFKI-NLP/faq-rewrites-llms](https://github.com/DFKI-NLP/faq-rewrites-llms)."