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data/2402.14848.json

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+{"paper_url": "https://huggingface.co/papers/2402.14848", "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* [Remember This Event That Year? Assessing Temporal Information and Reasoning in Large Language Models](https://huggingface.co/papers/2402.11997) (2024)\n* [CIF-Bench: A Chinese Instruction-Following Benchmark for Evaluating the Generalizability of Large Language Models](https://huggingface.co/papers/2402.13109) (2024)\n* [Why Lift so Heavy? Slimming Large Language Models by Cutting Off the Layers](https://huggingface.co/papers/2402.11700) (2024)\n* [$\\infty$Bench: Extending Long Context Evaluation Beyond 100K Tokens](https://huggingface.co/papers/2402.13718) (2024)\n* [Tiny Titans: Can Smaller Large Language Models Punch Above Their Weight in the Real World for Meeting Summarization?](https://huggingface.co/papers/2402.00841) (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/2402.14905.json

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+{"paper_url": "https://huggingface.co/papers/2402.14905", "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* [Head-wise Shareable Attention for Large Language Models](https://huggingface.co/papers/2402.11819) (2024)\n* [Why Lift so Heavy? Slimming Large Language Models by Cutting Off the Layers](https://huggingface.co/papers/2402.11700) (2024)\n* [Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs](https://huggingface.co/papers/2402.10517) (2024)\n* [BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models](https://huggingface.co/papers/2402.11573) (2024)\n* [Rethinking Optimization and Architecture for Tiny Language Models](https://huggingface.co/papers/2402.02791) (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/2402.15000.json

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+{"paper_url": "https://huggingface.co/papers/2402.15000", "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* [Divide and Conquer for Large Language Models Reasoning](https://huggingface.co/papers/2401.05190) (2024)\n* [Guiding Large Language Models with Divide-and-Conquer Program for Discerning Problem Solving](https://huggingface.co/papers/2402.05359) (2024)\n* [TinyLLM: Learning a Small Student from Multiple Large Language Models](https://huggingface.co/papers/2402.04616) (2024)\n* [Distilling Mathematical Reasoning Capabilities into Small Language Models](https://huggingface.co/papers/2401.11864) (2024)\n* [AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition](https://huggingface.co/papers/2402.11452) (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/2402.15021.json

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+{"paper_url": "https://huggingface.co/papers/2402.15021", "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* [Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning](https://huggingface.co/papers/2402.11690) (2024)\n* [MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark](https://huggingface.co/papers/2402.04788) (2024)\n* [Prometheus-Vision: Vision-Language Model as a Judge for Fine-Grained Evaluation](https://huggingface.co/papers/2401.06591) (2024)\n* [Efficient Multimodal Learning from Data-centric Perspective](https://huggingface.co/papers/2402.11530) (2024)\n* [GPT4Ego: Unleashing the Potential of Pre-trained Models for Zero-Shot Egocentric Action Recognition](https://huggingface.co/papers/2401.10039) (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/2402.15220.json

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+{"paper_url": "https://huggingface.co/papers/2402.15220", "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* [Hydragen: High-Throughput LLM Inference with Shared Prefixes](https://huggingface.co/papers/2402.05099) (2024)\n* [RelayAttention for Efficient Large Language Model Serving with Long System Prompts](https://huggingface.co/papers/2402.14808) (2024)\n* [APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding](https://huggingface.co/papers/2401.06761) (2024)\n* [KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache](https://huggingface.co/papers/2402.02750) (2024)\n* [DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference](https://huggingface.co/papers/2401.08671) (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/2402.15391.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2402.15391", "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* [Large-Scale Actionless Video Pre-Training via Discrete Diffusion for Efficient Policy Learning](https://huggingface.co/papers/2402.14407) (2024)\n* [Compositional Generative Modeling: A Single Model is Not All You Need](https://huggingface.co/papers/2402.01103) (2024)\n* [Collaboratively Self-supervised Video Representation Learning for Action Recognition](https://huggingface.co/papers/2401.07584) (2024)\n* [An Interactive Agent Foundation Model](https://huggingface.co/papers/2402.05929) (2024)\n* [Generative Human Motion Stylization in Latent Space](https://huggingface.co/papers/2401.13505) (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/2402.15491.json

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+{"paper_url": "https://huggingface.co/papers/2402.15491", "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* [ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios](https://huggingface.co/papers/2401.00741) (2024)\n* [API Pack: A Massive Multilingual Dataset for API Call Generation](https://huggingface.co/papers/2402.09615) (2024)\n* [DataDreamer: A Tool for Synthetic Data Generation and Reproducible LLM Workflows](https://huggingface.co/papers/2402.10379) (2024)\n* [TOOLVERIFIER: Generalization to New Tools via Self-Verification](https://huggingface.co/papers/2402.14158) (2024)\n* [APIGen: Generative API Method Recommendation](https://huggingface.co/papers/2401.15843) (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/2402.15506.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2402.15506", "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* [Large Language Model Agent for Hyper-Parameter Optimization](https://huggingface.co/papers/2402.01881) (2024)\n* [Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects](https://huggingface.co/papers/2401.03428) (2024)\n* [An Interactive Agent Foundation Model](https://huggingface.co/papers/2402.05929) (2024)\n* [Breaking Data Silos: Cross-Domain Learning for Multi-Agent Perception from Independent Private Sources](https://huggingface.co/papers/2402.04273) (2024)\n* [Neeko: Leveraging Dynamic LoRA for Efficient Multi-Character Role-Playing Agent](https://huggingface.co/papers/2402.13717) (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`"}