Scheduled Commit

data/2410.11711.json

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+{"paper_url": "https://huggingface.co/papers/2410.11711", "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* [Masked Generative Priors Improve World Models Sequence Modelling Capabilities](https://huggingface.co/papers/2410.07836) (2024)\n* [Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models](https://huggingface.co/papers/2410.01280) (2024)\n* [MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL](https://huggingface.co/papers/2410.08896) (2024)\n* [Reward-free World Models for Online Imitation Learning](https://huggingface.co/papers/2410.14081) (2024)\n* [Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining](https://huggingface.co/papers/2410.00564) (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/2410.12788.json

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+{"paper_url": "https://huggingface.co/papers/2410.12788", "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* [ChuLo: Chunk-Level Key Information Representation for Long Document Processing](https://huggingface.co/papers/2410.11119) (2024)\n* [E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning](https://huggingface.co/papers/2409.06679) (2024)\n* [CoFE-RAG: A Comprehensive Full-chain Evaluation Framework for Retrieval-Augmented Generation with Enhanced Data Diversity](https://huggingface.co/papers/2410.12248) (2024)\n* [Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding Models](https://huggingface.co/papers/2409.04701) (2024)\n* [Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs](https://huggingface.co/papers/2410.11001) (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/2410.13184.json

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+{"paper_url": "https://huggingface.co/papers/2410.13184", "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* [FiRST: Finetuning Router-Selective Transformers for Input-Adaptive Latency Reduction](https://huggingface.co/papers/2410.12513) (2024)\n* [CFSP: An Efficient Structured Pruning Framework for LLMs with Coarse-to-Fine Activation Information](https://huggingface.co/papers/2409.13199) (2024)\n* [SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model Transformation](https://huggingface.co/papers/2410.03960) (2024)\n* [Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models](https://huggingface.co/papers/2410.11772) (2024)\n* [Duo-LLM: A Framework for Studying Adaptive Computation in Large Language Models](https://huggingface.co/papers/2410.10846) (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/2410.13218.json

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+{"paper_url": "https://huggingface.co/papers/2410.13218", "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* [Multi-Session Client-Centered Treatment Outcome Evaluation in Psychotherapy](https://huggingface.co/papers/2410.05824) (2024)\n* [MentalArena: Self-play Training of Language Models for Diagnosis and Treatment of Mental Health Disorders](https://huggingface.co/papers/2410.06845) (2024)\n* [Therapy as an NLP Task: Psychologists' Comparison of LLMs and Human Peers in CBT](https://huggingface.co/papers/2409.02244) (2024)\n* [Interactive Agents: Simulating Counselor-Client Psychological Counseling via Role-Playing LLM-to-LLM Interactions](https://huggingface.co/papers/2408.15787) (2024)\n* [TheraGen: Therapy for Every Generation](https://huggingface.co/papers/2409.13748) (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/2410.13394.json

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+{"paper_url": "https://huggingface.co/papers/2410.13394", "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* [Language Imbalance Driven Rewarding for Multilingual Self-improving](https://huggingface.co/papers/2410.08964) (2024)\n* [L3Cube-IndicQuest: A Benchmark Questing Answering Dataset for Evaluating Knowledge of LLMs in Indic Context](https://huggingface.co/papers/2409.08706) (2024)\n* [Cross-lingual Transfer for Automatic Question Generation by Learning Interrogative Structures in Target Languages](https://huggingface.co/papers/2410.03197) (2024)\n* [ReIFE: Re-evaluating Instruction-Following Evaluation](https://huggingface.co/papers/2410.07069) (2024)\n* [Direct Judgement Preference Optimization](https://huggingface.co/papers/2409.14664) (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/2410.13861.json

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+{"paper_url": "https://huggingface.co/papers/2410.13861", "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* [Croc: Pretraining Large Multimodal Models with Cross-Modal Comprehension](https://huggingface.co/papers/2410.14332) (2024)\n* [Instruction-guided Multi-Granularity Segmentation and Captioning with Large Multimodal Model](https://huggingface.co/papers/2409.13407) (2024)\n* [OmniBooth: Learning Latent Control for Image Synthesis with Multi-modal Instruction](https://huggingface.co/papers/2410.04932) (2024)\n* [MMFuser: Multimodal Multi-Layer Feature Fuser for Fine-Grained Vision-Language Understanding](https://huggingface.co/papers/2410.11829) (2024)\n* [VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation](https://huggingface.co/papers/2409.04429) (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/2410.14086.json

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+{"paper_url": "https://huggingface.co/papers/2410.14086", "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* [In-context Learning in Presence of Spurious Correlations](https://huggingface.co/papers/2410.03140) (2024)\n* [Can In-context Learning Really Generalize to Out-of-distribution Tasks?](https://huggingface.co/papers/2410.09695) (2024)\n* [Bayes' Power for Explaining In-Context Learning Generalizations](https://huggingface.co/papers/2410.01565) (2024)\n* [Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis](https://huggingface.co/papers/2410.02167) (2024)\n* [Task Diversity Shortens the ICL Plateau](https://huggingface.co/papers/2410.05448) (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/2410.14745.json

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+{"paper_url": "https://huggingface.co/papers/2410.14745", "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* [SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe](https://huggingface.co/papers/2410.05248) (2024)\n* [On Unsupervised Prompt Learning for Classification with Black-box Language Models](https://huggingface.co/papers/2410.03124) (2024)\n* [Mixing It Up: The Cocktail Effect of Multi-Task Fine-Tuning on LLM Performance -- A Case Study in Finance](https://huggingface.co/papers/2410.01109) (2024)\n* [PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches](https://huggingface.co/papers/2410.10870) (2024)\n* [Empirical Insights on Fine-Tuning Large Language Models for Question-Answering](https://huggingface.co/papers/2409.15825) (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/2410.14940.json

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+{"paper_url": "https://huggingface.co/papers/2410.14940", "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* [SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding](https://huggingface.co/papers/2408.15545) (2024)\n* [Data-Efficient Massive Tool Retrieval: A Reinforcement Learning Approach for Query-Tool Alignment with Language Models](https://huggingface.co/papers/2410.03212) (2024)\n* [KodeXv0.1: A Family of State-of-the-Art Financial Large Language Models](https://huggingface.co/papers/2409.13749) (2024)\n* [GenCRF: Generative Clustering and Reformulation Framework for Enhanced Intent-Driven Information Retrieval](https://huggingface.co/papers/2409.10909) (2024)\n* [Packing Analysis: Packing Is More Appropriate for Large Models or Datasets in Supervised Fine-tuning](https://huggingface.co/papers/2410.08081) (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/2410.15002.json

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+{"paper_url": "https://huggingface.co/papers/2410.15002", "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* [Embedding an Ethical Mind: Aligning Text-to-Image Synthesis via Lightweight Value Optimization](https://huggingface.co/papers/2410.12700) (2024)\n* [In Search of Forgotten Domain Generalization](https://huggingface.co/papers/2410.08258) (2024)\n* [LoTLIP: Improving Language-Image Pre-training for Long Text Understanding](https://huggingface.co/papers/2410.05249) (2024)\n* [ArtiFade: Learning to Generate High-quality Subject from Blemished Images](https://huggingface.co/papers/2409.03745) (2024)\n* [One-Shot Learning for Pose-Guided Person Image Synthesis in the Wild](https://huggingface.co/papers/2409.09593) (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/2410.15017.json

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+{"paper_url": "https://huggingface.co/papers/2410.15017", "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* [Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model](https://huggingface.co/papers/2408.17175) (2024)\n* [WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling](https://huggingface.co/papers/2408.16532) (2024)\n* [Investigating Neural Audio Codecs for Speech Language Model-Based Speech Generation](https://huggingface.co/papers/2409.04016) (2024)\n* [Analyzing and Mitigating Inconsistency in Discrete Audio Tokens for Neural Codec Language Models](https://huggingface.co/papers/2409.19283) (2024)\n* [Recent Advances in Speech Language Models: A Survey](https://huggingface.co/papers/2410.03751) (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/2410.15316.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2410.15316", "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* [IntrinsicVoice: Empowering LLMs with Intrinsic Real-time Voice Interaction Abilities](https://huggingface.co/papers/2410.08035) (2024)\n* [Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming](https://huggingface.co/papers/2408.16725) (2024)\n* [SSR: Alignment-Aware Modality Connector for Speech Language Models](https://huggingface.co/papers/2410.00168) (2024)\n* [Recent Advances in Speech Language Models: A Survey](https://huggingface.co/papers/2410.03751) (2024)\n* [Self-Powered LLM Modality Expansion for Large Speech-Text Models](https://huggingface.co/papers/2410.03798) (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/2410.15460.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2410.15460", "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* [Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding](https://huggingface.co/papers/2410.13321) (2024)\n* [FactCheckmate: Preemptively Detecting and Mitigating Hallucinations in LMs](https://huggingface.co/papers/2410.02899) (2024)\n* [MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation](https://huggingface.co/papers/2410.11779) (2024)\n* [HALO: Hallucination Analysis and Learning Optimization to Empower LLMs with Retrieval-Augmented Context for Guided Clinical Decision Making](https://huggingface.co/papers/2409.10011) (2024)\n* [ConVis: Contrastive Decoding with Hallucination Visualization for Mitigating Hallucinations in Multimodal Large Language Models](https://huggingface.co/papers/2408.13906) (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/2410.15633.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2410.15633", "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* [What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices](https://huggingface.co/papers/2409.01893) (2024)\n* [Untie the Knots: An Efficient Data Augmentation Strategy for Long-Context Pre-Training in Language Models](https://huggingface.co/papers/2409.04774) (2024)\n* [Enhancing and Accelerating Large Language Models via Instruction-Aware Contextual Compression](https://huggingface.co/papers/2408.15491) (2024)\n* [Minimum Tuning to Unlock Long Output from LLMs with High Quality Data as the Key](https://huggingface.co/papers/2410.10210) (2024)\n* [LongGenBench: Benchmarking Long-Form Generation in Long Context LLMs](https://huggingface.co/papers/2409.02076) (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/2410.15735.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2410.15735", "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* [Mechanistic Behavior Editing of Language Models](https://huggingface.co/papers/2410.04277) (2024)\n* [Automatically Interpreting Millions of Features in Large Language Models](https://huggingface.co/papers/2410.13928) (2024)\n* [TransformerRanker: A Tool for Efficiently Finding the Best-Suited Language Models for Downstream Classification Tasks](https://huggingface.co/papers/2409.05997) (2024)\n* [Harnessing the Intrinsic Knowledge of Pretrained Language Models for Challenging Text Classification Settings](https://huggingface.co/papers/2408.15650) (2024)\n* [LOLA - An Open-Source Massively Multilingual Large Language Model](https://huggingface.co/papers/2409.11272) (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/2410.15748.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2410.15748", "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* [Herald: A Natural Language Annotated Lean 4 Dataset](https://huggingface.co/papers/2410.10878) (2024)\n* [AI for Mathematics Mathematical Formalized Problem Solving and Theorem Proving in Different Fields in Lean4](https://huggingface.co/papers/2409.05977) (2024)\n* [LeanAgent: Lifelong Learning for Formal Theorem Proving](https://huggingface.co/papers/2410.06209) (2024)\n* [Proof Flow: Preliminary Study on Generative Flow Network Language Model Tuning for Formal Reasoning](https://huggingface.co/papers/2410.13224) (2024)\n* [AlphaIntegrator: Transformer Action Search for Symbolic Integration Proofs](https://huggingface.co/papers/2410.02666) (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`"}