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data/2405.17052.json

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+{"paper_url": "https://huggingface.co/papers/2405.17052", "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* [Unifying Demonstration Selection and Compression for In-Context Learning](https://huggingface.co/papers/2405.17062) (2024)\n* [AIM: Let Any Multi-modal Large Language Models Embrace Efficient In-Context Learning](https://huggingface.co/papers/2406.07588) (2024)\n* [Recurrent Context Compression: Efficiently Expanding the Context Window of LLM](https://huggingface.co/papers/2406.06110) (2024)\n* [Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs](https://huggingface.co/papers/2406.02376) (2024)\n* [IAPT: Instruction-Aware Prompt Tuning for Large Language Models](https://huggingface.co/papers/2405.18203) (2024)\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`"}

data/2406.02376.json

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+{"paper_url": "https://huggingface.co/papers/2406.02376", "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* [Recurrent Context Compression: Efficiently Expanding the Context Window of LLM](https://huggingface.co/papers/2406.06110) (2024)\n* [SelfCP: Compressing Long Prompt to 1/12 Using the Frozen Large Language Model Itself](https://huggingface.co/papers/2405.17052) (2024)\n* [Unifying Demonstration Selection and Compression for In-Context Learning](https://huggingface.co/papers/2405.17062) (2024)\n* [LoCoCo: Dropping In Convolutions for Long Context Compression](https://huggingface.co/papers/2406.05317) (2024)\n* [An Information Bottleneck Perspective for Effective Noise Filtering on Retrieval-Augmented Generation](https://huggingface.co/papers/2406.01549) (2024)\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`"}