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data/2402.00159.json

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+{"paper_url": "https://huggingface.co/papers/2402.00159", "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* [TinyLlama: An Open-Source Small Language Model](https://huggingface.co/papers/2401.02385) (2024)\n* [Improving Natural Language Capability of Code Large Language Model](https://huggingface.co/papers/2401.14242) (2024)\n* [MaLA-500: Massive Language Adaptation of Large Language Models](https://huggingface.co/papers/2401.13303) (2024)\n* [Orion-14B: Open-source Multilingual Large Language Models](https://huggingface.co/papers/2401.12246) (2024)\n* [LLaMA Beyond English: An Empirical Study on Language Capability Transfer](https://huggingface.co/papers/2401.01055) (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/2402.00351.json

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+{"paper_url": "https://huggingface.co/papers/2402.00351", "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* [Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models](https://huggingface.co/papers/2312.14923) (2023)\n* [FAST: Feature Aware Similarity Thresholding for Weak Unlearning in Black-Box Generative Models](https://huggingface.co/papers/2312.14895) (2023)\n* [DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations](https://huggingface.co/papers/2401.12517) (2024)\n* [Black-box Membership Inference Attacks against Fine-tuned Diffusion Models](https://huggingface.co/papers/2312.08207) (2023)\n* [Class-Prototype Conditional Diffusion Model for Continual Learning with Generative Replay](https://huggingface.co/papers/2312.06710) (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`"}

data/2402.00396.json

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+{"paper_url": "https://huggingface.co/papers/2402.00396", "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* [West-of-N: Synthetic Preference Generation for Improved Reward Modeling](https://huggingface.co/papers/2401.12086) (2024)\n* [Improving Reinforcement Learning from Human Feedback with Efficient Reward Model Ensemble](https://huggingface.co/papers/2401.16635) (2024)\n* [Uncertainty-Penalized Reinforcement Learning from Human Feedback with Diverse Reward LoRA Ensembles](https://huggingface.co/papers/2401.00243) (2023)\n* [Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF](https://huggingface.co/papers/2401.16335) (2024)\n* [Secrets of RLHF in Large Language Models Part II: Reward Modeling](https://huggingface.co/papers/2401.06080) (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/2402.00518.json

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+{"paper_url": "https://huggingface.co/papers/2402.00518", "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* [EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism](https://huggingface.co/papers/2312.04916) (2023)\n* [HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy](https://huggingface.co/papers/2401.15207) (2024)\n* [Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks](https://huggingface.co/papers/2401.02731) (2024)\n* [Understanding LLMs: A Comprehensive Overview from Training to Inference](https://huggingface.co/papers/2401.02038) (2024)\n* [Impact of Tokenization on LLaMa Russian Adaptation](https://huggingface.co/papers/2312.02598) (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`"}

data/2402.00742.json

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+{"paper_url": "https://huggingface.co/papers/2402.00742", "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* [Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking](https://huggingface.co/papers/2312.09244) (2023)\n* [West-of-N: Synthetic Preference Generation for Improved Reward Modeling](https://huggingface.co/papers/2401.12086) (2024)\n* [Secrets of RLHF in Large Language Models Part II: Reward Modeling](https://huggingface.co/papers/2401.06080) (2024)\n* [WARM: On the Benefits of Weight Averaged Reward Models](https://huggingface.co/papers/2401.12187) (2024)\n* [ULMA: Unified Language Model Alignment with Demonstration and Point-wise Human Preference](https://huggingface.co/papers/2312.02554) (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`"}

data/2402.00769.json

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+{"paper_url": "https://huggingface.co/papers/2402.00769", "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* [VideoLCM: Video Latent Consistency Model](https://huggingface.co/papers/2312.09109) (2023)\n* [SpeedUpNet: A Plug-and-Play Hyper-Network for Accelerating Text-to-Image Diffusion Models](https://huggingface.co/papers/2312.08887) (2023)\n* [DreamVideo: Composing Your Dream Videos with Customized Subject and Motion](https://huggingface.co/papers/2312.04433) (2023)\n* [BIVDiff: A Training-Free Framework for General-Purpose Video Synthesis via Bridging Image and Video Diffusion Models](https://huggingface.co/papers/2312.02813) (2023)\n* [Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling](https://huggingface.co/papers/2401.15977) (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/2402.00786.json

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+{"paper_url": "https://huggingface.co/papers/2402.00786", "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* [TeenyTinyLlama: open-source tiny language models trained in Brazilian Portuguese](https://huggingface.co/papers/2401.16640) (2024)\n* [TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generation](https://huggingface.co/papers/2401.14373) (2024)\n* [TinyLlama: An Open-Source Small Language Model](https://huggingface.co/papers/2401.02385) (2024)\n* [Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling](https://huggingface.co/papers/2401.16380) (2024)\n* [Orion-14B: Open-source Multilingual Large Language Models](https://huggingface.co/papers/2401.12246) (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/2402.00838.json

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+{"paper_url": "https://huggingface.co/papers/2402.00838", "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* [LLM360: Towards Fully Transparent Open-Source LLMs](https://huggingface.co/papers/2312.06550) (2023)\n* [Paloma: A Benchmark for Evaluating Language Model Fit](https://huggingface.co/papers/2312.10523) (2023)\n* [TinyLlama: An Open-Source Small Language Model](https://huggingface.co/papers/2401.02385) (2024)\n* [DeepSeek LLM: Scaling Open-Source Language Models with Longtermism](https://huggingface.co/papers/2401.02954) (2024)\n* [Catwalk: A Unified Language Model Evaluation Framework for Many Datasets](https://huggingface.co/papers/2312.10253) (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`"}

data/2402.00854.json

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+{"paper_url": "https://huggingface.co/papers/2402.00854", "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* [Bridging Logic and Learning: A Neural-Symbolic Approach for Enhanced Reasoning in Neural Models (ASPER)](https://huggingface.co/papers/2312.11651) (2023)\n* [Probabilistic Abduction for Visual Abstract Reasoning via Learning Rules in Vector-symbolic Architectures](https://huggingface.co/papers/2401.16024) (2024)\n* [On the verification of Embeddings using Hybrid Markov Logic](https://huggingface.co/papers/2312.08287) (2023)\n* [Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion](https://huggingface.co/papers/2401.12947) (2024)\n* [LangProp: A code optimization framework using Language Models applied to driving](https://huggingface.co/papers/2401.10314) (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/2402.00858.json

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+{"paper_url": "https://huggingface.co/papers/2402.00858", "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* [Supervised Knowledge Makes Large Language Models Better In-context Learners](https://huggingface.co/papers/2312.15918) (2023)\n* [Evaluating Large Language Models in Semantic Parsing for Conversational Question Answering over Knowledge Graphs](https://huggingface.co/papers/2401.01711) (2024)\n* [INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning](https://huggingface.co/papers/2401.06532) (2024)\n* [PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities](https://huggingface.co/papers/2401.07078) (2024)\n* [kNN-ICL: Compositional Task-Oriented Parsing Generalization with Nearest Neighbor In-Context Learning](https://huggingface.co/papers/2312.10771) (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`"}

data/2402.00867.json

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+{"paper_url": "https://huggingface.co/papers/2402.00867", "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* [HexaGen3D: StableDiffusion is just one step away from Fast and Diverse Text-to-3D Generation](https://huggingface.co/papers/2401.07727) (2024)\n* [Text-to-3D Generation with Bidirectional Diffusion using both 2D and 3D priors](https://huggingface.co/papers/2312.04963) (2023)\n* [PI3D: Efficient Text-to-3D Generation with Pseudo-Image Diffusion](https://huggingface.co/papers/2312.09069) (2023)\n* [4DGen: Grounded 4D Content Generation with Spatial-temporal Consistency](https://huggingface.co/papers/2312.17225) (2023)\n* [TPA3D: Triplane Attention for Fast Text-to-3D Generation](https://huggingface.co/papers/2312.02647) (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`"}