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data/2411.10442.json

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+{"paper_url": "https://huggingface.co/papers/2411.10442", "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* [CodePMP: Scalable Preference Model Pretraining for Large Language Model Reasoning](https://huggingface.co/papers/2410.02229) (2024)\n* [Improve Vision Language Model Chain-of-thought Reasoning](https://huggingface.co/papers/2410.16198) (2024)\n* [Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback](https://huggingface.co/papers/2410.03145) (2024)\n* [SymDPO: Boosting In-Context Learning of Large Multimodal Models with Symbol Demonstration Direct Preference Optimization](https://huggingface.co/papers/2411.11909) (2024)\n* [Vision-Language Models Can Self-Improve Reasoning via Reflection](https://huggingface.co/papers/2411.00855) (2024)\n* [MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models](https://huggingface.co/papers/2410.17637) (2024)\n* [MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning](https://huggingface.co/papers/2409.20566) (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/2411.12364.json

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+{"paper_url": "https://huggingface.co/papers/2411.12364", "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* [Sparse Upcycling: Inference Inefficient Finetuning](https://huggingface.co/papers/2411.08968) (2024)\n* [FluidML: Fast and Memory Efficient Inference Optimization](https://huggingface.co/papers/2411.09242) (2024)\n* [Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix](https://huggingface.co/papers/2410.11261) (2024)\n* [Communication Compression for Tensor Parallel LLM Inference](https://huggingface.co/papers/2411.09510) (2024)\n* [ED-ViT: Splitting Vision Transformer for Distributed Inference on Edge Devices](https://huggingface.co/papers/2410.11650) (2024)\n* [SLiM: One-shot Quantized Sparse Plus Low-rank Approximation of LLMs](https://huggingface.co/papers/2410.09615) (2024)\n* [Learning Parameter Sharing with Tensor Decompositions and Sparsity](https://huggingface.co/papers/2411.09816) (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/2411.13082.json

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+{"paper_url": "https://huggingface.co/papers/2411.13082", "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* [SuperCorrect: Supervising and Correcting Language Models with Error-Driven Insights](https://huggingface.co/papers/2410.09008) (2024)\n* [PersonaMath: Enhancing Math Reasoning through Persona-Driven Data Augmentation](https://huggingface.co/papers/2410.01504) (2024)\n* [AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning](https://huggingface.co/papers/2411.11930) (2024)\n* [A Comparative Study on Reasoning Patterns of OpenAI's o1 Model](https://huggingface.co/papers/2410.13639) (2024)\n* [Vision-Language Models Can Self-Improve Reasoning via Reflection](https://huggingface.co/papers/2411.00855) (2024)\n* [BEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search](https://huggingface.co/papers/2409.17972) (2024)\n* [Step Guided Reasoning: Improving Mathematical Reasoning using Guidance Generation and Step Reasoning](https://huggingface.co/papers/2410.19817) (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/2411.13676.json

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+{"paper_url": "https://huggingface.co/papers/2411.13676", "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* [Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions](https://huggingface.co/papers/2410.06577) (2024)\n* [Taipan: Efficient and Expressive State Space Language Models with Selective Attention](https://huggingface.co/papers/2410.18572) (2024)\n* [DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads](https://huggingface.co/papers/2410.10819) (2024)\n* [A Little Goes a Long Way: Efficient Long Context Training and Inference with Partial Contexts](https://huggingface.co/papers/2410.01485) (2024)\n* [TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection](https://huggingface.co/papers/2411.02886) (2024)\n* [Falcon Mamba: The First Competitive Attention-free 7B Language Model](https://huggingface.co/papers/2410.05355) (2024)\n* [In-context KV-Cache Eviction for LLMs via Attention-Gate](https://huggingface.co/papers/2410.12876) (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/2411.13807.json

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+{"paper_url": "https://huggingface.co/papers/2411.13807", "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* [DriveDreamer4D: World Models Are Effective Data Machines for 4D Driving Scene Representation](https://huggingface.co/papers/2410.13571) (2024)\n* [Exploring the Interplay Between Video Generation and World Models in Autonomous Driving: A Survey](https://huggingface.co/papers/2411.02914) (2024)\n* [The Dawn of Video Generation: Preliminary Explorations with SORA-like Models](https://huggingface.co/papers/2410.05227) (2024)\n* [Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep Approach](https://huggingface.co/papers/2410.03160) (2024)\n* [LumiSculpt: A Consistency Lighting Control Network for Video Generation](https://huggingface.co/papers/2410.22979) (2024)\n* [LaVida Drive: Vision-Text Interaction VLM for Autonomous Driving with Token Selection, Recovery and Enhancement](https://huggingface.co/papers/2411.12980) (2024)\n* [DrivingSphere: Building a High-fidelity 4D World for Closed-loop Simulation](https://huggingface.co/papers/2411.11252) (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/2411.14199.json

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+{"paper_url": "https://huggingface.co/papers/2411.14199", "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* [Sufficient Context: A New Lens on Retrieval Augmented Generation Systems](https://huggingface.co/papers/2411.06037) (2024)\n* [Assessing the Answerability of Queries in Retrieval-Augmented Code Generation](https://huggingface.co/papers/2411.05547) (2024)\n* [Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models](https://huggingface.co/papers/2410.01782) (2024)\n* [Query Optimization for Parametric Knowledge Refinement in Retrieval-Augmented Large Language Models](https://huggingface.co/papers/2411.07820) (2024)\n* [SciDQA: A Deep Reading Comprehension Dataset over Scientific Papers](https://huggingface.co/papers/2411.05338) (2024)\n* [LLM-Ref: Enhancing Reference Handling in Technical Writing with Large Language Models](https://huggingface.co/papers/2411.00294) (2024)\n* [Large Language Models Can Self-Improve in Long-context Reasoning](https://huggingface.co/papers/2411.08147) (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/2411.14251.json

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+{"paper_url": "https://huggingface.co/papers/2411.14251", "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* [Improving the Language Understanding Capabilities of Large Language Models Using Reinforcement Learning](https://huggingface.co/papers/2410.11020) (2024)\n* [On the Modeling Capabilities of Large Language Models for Sequential Decision Making](https://huggingface.co/papers/2410.05656) (2024)\n* [Teaching Embodied Reinforcement Learning Agents: Informativeness and Diversity of Language Use](https://huggingface.co/papers/2410.24218) (2024)\n* [From Reward Shaping to Q-Shaping: Achieving Unbiased Learning with LLM-Guided Knowledge](https://huggingface.co/papers/2410.01458) (2024)\n* [MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions](https://huggingface.co/papers/2410.02743) (2024)\n* [Enhancing Multi-Step Reasoning Abilities of Language Models through Direct Q-Function Optimization](https://huggingface.co/papers/2410.09302) (2024)\n* [Words as Beacons: Guiding RL Agents with High-Level Language Prompts](https://huggingface.co/papers/2410.08632) (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/2411.14257.json

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+{"paper_url": "https://huggingface.co/papers/2411.14257", "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* [LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations](https://huggingface.co/papers/2410.02707) (2024)\n* [ReDeEP: Detecting Hallucination in Retrieval-Augmented Generation via Mechanistic Interpretability](https://huggingface.co/papers/2410.11414) (2024)\n* [Distinguishing Ignorance from Error in LLM Hallucinations](https://huggingface.co/papers/2410.22071) (2024)\n* [Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations](https://huggingface.co/papers/2410.02762) (2024)\n* [DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate Hallucinations](https://huggingface.co/papers/2410.18860) (2024)\n* [MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation](https://huggingface.co/papers/2410.11779) (2024)\n* [Reducing Hallucinations in Vision-Language Models via Latent Space Steering](https://huggingface.co/papers/2410.15778) (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/2411.14343.json

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+{"paper_url": "https://huggingface.co/papers/2411.14343", "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* [A Survey of Small Language Models](https://huggingface.co/papers/2410.20011) (2024)\n* [SPRING Lab IITM's Submission to Low Resource Indic Language Translation Shared Task](https://huggingface.co/papers/2411.00727) (2024)\n* [Adapting Multilingual LLMs to Low-Resource Languages using Continued Pre-training and Synthetic Corpus](https://huggingface.co/papers/2410.14815) (2024)\n* [Think Carefully and Check Again! Meta-Generation Unlocking LLMs for Low-Resource Cross-Lingual Summarization](https://huggingface.co/papers/2410.20021) (2024)\n* [BongLLaMA: LLaMA for Bangla Language](https://huggingface.co/papers/2410.21200) (2024)\n* [EMMA-500: Enhancing Massively Multilingual Adaptation of Large Language Models](https://huggingface.co/papers/2409.17892) (2024)\n* [A Practical Guide to Fine-tuning Language Models with Limited Data](https://huggingface.co/papers/2411.09539) (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/2411.14347.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.14347", "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* [Training-Free Open-Ended Object Detection and Segmentation via Attention as Prompts](https://huggingface.co/papers/2410.05963) (2024)\n* [UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentation](https://huggingface.co/papers/2411.08569) (2024)\n* [Open-set object detection: towards unified problem formulation and benchmarking](https://huggingface.co/papers/2411.05564) (2024)\n* [Boosting Open-Vocabulary Object Detection by Handling Background Samples](https://huggingface.co/papers/2410.08645) (2024)\n* [CASA: Class-Agnostic Shared Attributes in Vision-Language Models for Efficient Incremental Object Detection](https://huggingface.co/papers/2410.05804) (2024)\n* [ViTOC: Vision Transformer and Object-aware Captioner](https://huggingface.co/papers/2411.07265) (2024)\n* [Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation](https://huggingface.co/papers/2411.09219) (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/2411.14384.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.14384", "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* [VistaDream: Sampling multiview consistent images for single-view scene reconstruction](https://huggingface.co/papers/2410.16892) (2024)\n* [Direct and Explicit 3D Generation from a Single Image](https://huggingface.co/papers/2411.10947) (2024)\n* [DiffPano: Scalable and Consistent Text to Panorama Generation with Spherical Epipolar-Aware Diffusion](https://huggingface.co/papers/2410.24203) (2024)\n* [Towards Multi-View Consistent Style Transfer with One-Step Diffusion via Vision Conditioning](https://huggingface.co/papers/2411.10130) (2024)\n* [MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views](https://huggingface.co/papers/2411.04924) (2024)\n* [3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D Generation](https://huggingface.co/papers/2410.18974) (2024)\n* [Generative Object Insertion in Gaussian Splatting with a Multi-View Diffusion Model](https://huggingface.co/papers/2409.16938) (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/2411.14402.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.14402", "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* [FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training](https://huggingface.co/papers/2411.11927) (2024)\n* [Contrastive Localized Language-Image Pre-Training](https://huggingface.co/papers/2410.02746) (2024)\n* [TripletCLIP: Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives](https://huggingface.co/papers/2411.02545) (2024)\n* [FoPru: Focal Pruning for Efficient Large Vision-Language Models](https://huggingface.co/papers/2411.14164) (2024)\n* [Improving Multi-modal Large Language Model through Boosting Vision Capabilities](https://huggingface.co/papers/2410.13733) (2024)\n* [RobustFormer: Noise-Robust Pre-training for images and videos](https://huggingface.co/papers/2411.13040) (2024)\n* [Understanding the Benefits of SimCLR Pre-Training in Two-Layer Convolutional Neural Networks](https://huggingface.co/papers/2409.18685) (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/2411.14405.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.14405", "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* [OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models](https://huggingface.co/papers/2410.09671) (2024)\n* [AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning](https://huggingface.co/papers/2411.11930) (2024)\n* [Reasoning Paths Optimization: Learning to Reason and Explore From Diverse Paths](https://huggingface.co/papers/2410.10858) (2024)\n* [LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning](https://huggingface.co/papers/2410.02884) (2024)\n* [Interpretable Contrastive Monte Carlo Tree Search Reasoning](https://huggingface.co/papers/2410.01707) (2024)\n* [DOTS: Learning to Reason Dynamically in LLMs via Optimal Reasoning Trajectories Search](https://huggingface.co/papers/2410.03864) (2024)\n* [Rational Metareasoning for Large Language Models](https://huggingface.co/papers/2410.05563) (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/2411.14430.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.14430", "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* [DiT4Edit: Diffusion Transformer for Image Editing](https://huggingface.co/papers/2411.03286) (2024)\n* [Vision-guided and Mask-enhanced Adaptive Denoising for Prompt-based Image Editing](https://huggingface.co/papers/2410.10496) (2024)\n* [Taming Rectified Flow for Inversion and Editing](https://huggingface.co/papers/2411.04746) (2024)\n* [OmniEdit: Building Image Editing Generalist Models Through Specialist Supervision](https://huggingface.co/papers/2411.07199) (2024)\n* [SeedEdit: Align Image Re-Generation to Image Editing](https://huggingface.co/papers/2411.06686) (2024)\n* [ReEdit: Multimodal Exemplar-Based Image Editing with Diffusion Models](https://huggingface.co/papers/2411.03982) (2024)\n* [Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution](https://huggingface.co/papers/2411.12072) (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/2411.14432.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2411.14432", "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* [LLaVA-o1: Let Vision Language Models Reason Step-by-Step](https://huggingface.co/papers/2411.10440) (2024)\n* [Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding](https://huggingface.co/papers/2411.04282) (2024)\n* [Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus](https://huggingface.co/papers/2411.12498) (2024)\n* [VisAidMath: Benchmarking Visual-Aided Mathematical Reasoning](https://huggingface.co/papers/2410.22995) (2024)\n* [Let's Be Self-generated via Step by Step: A Curriculum Learning Approach to Automated Reasoning with Large Language Models](https://huggingface.co/papers/2410.21728) (2024)\n* [ProReason: Multi-Modal Proactive Reasoning with Decoupled Eyesight and Wisdom](https://huggingface.co/papers/2410.14138) (2024)\n* [Proceedings of the First International Workshop on Next-Generation Language Models for Knowledge Representation and Reasoning (NeLaMKRR 2024)](https://huggingface.co/papers/2410.05339) (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`"}