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data/2408.13359.json

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+{"paper_url": "https://huggingface.co/papers/2408.13359", "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* [MaskMoE: Boosting Token-Level Learning via Routing Mask in Mixture-of-Experts](https://huggingface.co/papers/2407.09816) (2024)\n* [Scaling Law with Learning Rate Annealing](https://huggingface.co/papers/2408.11029) (2024)\n* [Layerwise Recurrent Router for Mixture-of-Experts](https://huggingface.co/papers/2408.06793) (2024)\n* [Reuse, Don't Retrain: A Recipe for Continued Pretraining of Language Models](https://huggingface.co/papers/2407.07263) (2024)\n* [Large Language Models as Foundations for Next-Gen Dense Retrieval: A Comprehensive Empirical Assessment](https://huggingface.co/papers/2408.12194) (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/2408.13413.json

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+{"paper_url": "https://huggingface.co/papers/2408.13413", "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* [FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention](https://huggingface.co/papers/2407.19918) (2024)\n* [Text-based Talking Video Editing with Cascaded Conditional Diffusion](https://huggingface.co/papers/2407.14841) (2024)\n* [Cinemo: Consistent and Controllable Image Animation with Motion Diffusion Models](https://huggingface.co/papers/2407.15642) (2024)\n* [FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance](https://huggingface.co/papers/2408.08189) (2024)\n* [Anchored Diffusion for Video Face Reenactment](https://huggingface.co/papers/2407.15153) (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/2408.13423.json

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+{"paper_url": "https://huggingface.co/papers/2408.13423", "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* [VEnhancer: Generative Space-Time Enhancement for Video Generation](https://huggingface.co/papers/2407.07667) (2024)\n* [FreeLong: Training-Free Long Video Generation with SpectralBlend Temporal Attention](https://huggingface.co/papers/2407.19918) (2024)\n* [FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidance](https://huggingface.co/papers/2408.08189) (2024)\n* [Noise Calibration: Plug-and-play Content-Preserving Video Enhancement using Pre-trained Video Diffusion Models](https://huggingface.co/papers/2407.10285) (2024)\n* [TrackGo: A Flexible and Efficient Method for Controllable Video Generation](https://huggingface.co/papers/2408.11475) (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/2408.13933.json

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+{"paper_url": "https://huggingface.co/papers/2408.13933", "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* [Mamba-PTQ: Outlier Channels in Recurrent Large Language Models](https://huggingface.co/papers/2407.12397) (2024)\n* [EfficientQAT: Efficient Quantization-Aware Training for Large Language Models](https://huggingface.co/papers/2407.11062) (2024)\n* [GPTQT: Quantize Large Language Models Twice to Push the Efficiency](https://huggingface.co/papers/2407.02891) (2024)\n* [ABQ-LLM: Arbitrary-Bit Quantized Inference Acceleration for Large Language Models](https://huggingface.co/papers/2408.08554) (2024)\n* [LeanQuant: Accurate Large Language Model Quantization with Loss-Error-Aware Grid](https://huggingface.co/papers/2407.10032) (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/2408.13934.json

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+{"paper_url": "https://huggingface.co/papers/2408.13934", "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* [Match Point AI: A Novel AI Framework for Evaluating Data-Driven Tennis Strategies](https://huggingface.co/papers/2408.05960) (2024)\n* [Personalized Dynamic Difficulty Adjustment -- Imitation Learning Meets Reinforcement Learning](https://huggingface.co/papers/2408.06818) (2024)\n* [Strategy and Skill Learning for Physics-based Table Tennis Animation](https://huggingface.co/papers/2407.16210) (2024)\n* [AMONGAGENTS: Evaluating Large Language Models in the Interactive Text-Based Social Deduction Game](https://huggingface.co/papers/2407.16521) (2024)\n* [People use fast, goal-directed simulation to reason about novel games](https://huggingface.co/papers/2407.14095) (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/2408.14211.json

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+{"paper_url": "https://huggingface.co/papers/2408.14211", "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* [SpaRP: Fast 3D Object Reconstruction and Pose Estimation from Sparse Views](https://huggingface.co/papers/2408.10195) (2024)\n* [Scene123: One Prompt to 3D Scene Generation via Video-Assisted and Consistency-Enhanced MAE](https://huggingface.co/papers/2408.05477) (2024)\n* [Cycle3D: High-quality and Consistent Image-to-3D Generation via Generation-Reconstruction Cycle](https://huggingface.co/papers/2407.19548) (2024)\n* [GenRC: Generative 3D Room Completion from Sparse Image Collections](https://huggingface.co/papers/2407.12939) (2024)\n* [TexGen: Text-Guided 3D Texture Generation with Multi-view Sampling and Resampling](https://huggingface.co/papers/2408.01291) (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/2408.14340.json

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+{"paper_url": "https://huggingface.co/papers/2408.14340", "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* [Reducing Barriers to the Use of Marginalised Music Genres in AI](https://huggingface.co/papers/2407.13439) (2024)\n* [Adversarial-MidiBERT: Symbolic Music Understanding Model Based on Unbias Pre-training and Mask Fine-tuning](https://huggingface.co/papers/2407.08306) (2024)\n* [Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspective](https://huggingface.co/papers/2408.04638) (2024)\n* [MelodyT5: A Unified Score-to-Score Transformer for Symbolic Music Processing](https://huggingface.co/papers/2407.02277) (2024)\n* [Explainability Paths for Sustained Artistic Practice with AI](https://huggingface.co/papers/2407.15216) (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/2408.14354.json

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+{"paper_url": "https://huggingface.co/papers/2408.14354", "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* [CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databases](https://huggingface.co/papers/2408.03910) (2024)\n* [DOMAINEVAL: An Auto-Constructed Benchmark for Multi-Domain Code Generation](https://huggingface.co/papers/2408.13204) (2024)\n* [What's Wrong with Your Code Generated by Large Language Models? An Extensive Study](https://huggingface.co/papers/2407.06153) (2024)\n* [KGym: A Platform and Dataset to Benchmark Large Language Models on Linux Kernel Crash Resolution](https://huggingface.co/papers/2407.02680) (2024)\n* [BLAZE: Cross-Language and Cross-Project Bug Localization via Dynamic Chunking and Hard Example Learning](https://huggingface.co/papers/2407.17631) (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/2408.14468.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2408.14468", "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* [Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arena](https://huggingface.co/papers/2407.10627) (2024)\n* [ViPer: Visual Personalization of Generative Models via Individual Preference Learning](https://huggingface.co/papers/2407.17365) (2024)\n* [Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization](https://huggingface.co/papers/2407.07880) (2024)\n* [Aligning Model Evaluations with Human Preferences: Mitigating Token Count Bias in Language Model Assessments](https://huggingface.co/papers/2407.12847) (2024)\n* [Compare without Despair: Reliable Preference Evaluation with Generation Separability](https://huggingface.co/papers/2407.01878) (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`"}