| {"paper_url": "https://huggingface.co/papers/2307.03172", "comment": "This is an automated message from the [Librarian Bot](https://huggingface.co/librarian-bots). I found the following papers similar to this paper. \n\nThe following papers were recommended by the Semantic Scholar API \n\n* [Marathon: A Race Through the Realm of Long Context with Large Language Models](https://huggingface.co/papers/2312.09542) (2023)\n* [\"Paraphrasing The Original Text\" Makes High Accuracy Long-Context QA](https://huggingface.co/papers/2312.11193) (2023)\n* [Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately](https://huggingface.co/papers/2402.01722) (2024)\n* [LongAlign: A Recipe for Long Context Alignment of Large Language Models](https://huggingface.co/papers/2401.18058) (2024)\n* [Structured Packing in LLM Training Improves Long Context Utilization](https://huggingface.co/papers/2312.17296) (2023)\n\n\n Please give a thumbs up to this comment if you found it helpful!\n\n If you want recommendations for any Paper on Hugging Face checkout [this](https://huggingface.co/spaces/librarian-bots/recommend_similar_papers) Space\n\n You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: `@librarian-bot recommend`"} |