Scheduled Commit

data/2504.18904.json

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+{"paper_url": "https://huggingface.co/papers/2504.18904", "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* [RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins](https://huggingface.co/papers/2504.13059) (2025)\n* [ReBot: Scaling Robot Learning with Real-to-Sim-to-Real Robotic Video Synthesis](https://huggingface.co/papers/2503.14526) (2025)\n* [AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems](https://huggingface.co/papers/2503.06669) (2025)\n* [Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation](https://huggingface.co/papers/2503.24361) (2025)\n* [Demonstrating DVS: Dynamic Virtual-Real Simulation Platform for Mobile Robotic Tasks](https://huggingface.co/papers/2504.18944) (2025)\n* [RL-Driven Data Generation for Robust Vision-Based Dexterous Grasping](https://huggingface.co/papers/2504.18084) (2025)\n* [Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering](https://huggingface.co/papers/2504.14135) (2025)\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/2504.19043.json

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+{"paper_url": "https://huggingface.co/papers/2504.19043", "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* [ConjointNet: Enhancing Conjoint Analysis for Preference Prediction with Representation Learning](https://huggingface.co/papers/2503.11710) (2025)\n* [Simultaneous elections in a polarized society make single-party sweeps more likely](https://huggingface.co/papers/2503.01663) (2025)\n* [Towards Multi-stakeholder Evaluation of ML Models: A Crowdsourcing Study on Metric Preferences in Job-Matching System](https://huggingface.co/papers/2503.05796) (2025)\n* [Regret Bounds for Robust Online Decision Making](https://huggingface.co/papers/2504.06820) (2025)\n* [HyperArm Bandit Optimization: A Novel approach to Hyperparameter Optimization and an Analysis of Bandit Algorithms in Stochastic and Adversarial Settings](https://huggingface.co/papers/2503.10282) (2025)\n* [Adaptive political surveys and GPT-4: Tackling the cold start problem with simulated user interactions](https://huggingface.co/papers/2503.09311) (2025)\n* [Preference-centric Bandits: Optimality of Mixtures and Regret-efficient Algorithms](https://huggingface.co/papers/2504.20877) (2025)\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/2504.19056.json

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+{"paper_url": "https://huggingface.co/papers/2504.19056", "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* [Generative AI for Film Creation: A Survey of Recent Advances](https://huggingface.co/papers/2504.08296) (2025)\n* [Spiritus: An AI-Assisted Tool for Creating 2D Characters and Animations](https://huggingface.co/papers/2503.09127) (2025)\n* [Survey of Video Diffusion Models: Foundations, Implementations, and Applications](https://huggingface.co/papers/2504.16081) (2025)\n* [MoCha: Towards Movie-Grade Talking Character Synthesis](https://huggingface.co/papers/2503.23307) (2025)\n* [Versatile Multimodal Controls for Expressive Talking Human Animation](https://huggingface.co/papers/2503.08714) (2025)\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/2504.19720.json

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+{"paper_url": "https://huggingface.co/papers/2504.19720", "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* [Seesaw: High-throughput LLM Inference via Model Re-sharding](https://huggingface.co/papers/2503.06433) (2025)\n* [DynaServe: Unified and Elastic Tandem-Style Execution for Dynamic Disaggregated LLM Serving](https://huggingface.co/papers/2504.09285) (2025)\n* [PIPO: Pipelined Offloading for Efficient Inference on Consumer Devices](https://huggingface.co/papers/2504.03664) (2025)\n* [HybriMoE: Hybrid CPU-GPU Scheduling and Cache Management for Efficient MoE Inference](https://huggingface.co/papers/2504.05897) (2025)\n* [Mind the Memory Gap: Unveiling GPU Bottlenecks in Large-Batch LLM Inference](https://huggingface.co/papers/2503.08311) (2025)\n* [Collaborative Speculative Inference for Efficient LLM Inference Serving](https://huggingface.co/papers/2503.10325) (2025)\n* [FastCache: Optimizing Multimodal LLM Serving through Lightweight KV-Cache Compression Framework](https://huggingface.co/papers/2503.08461) (2025)\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/2504.20708.json

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+{"paper_url": "https://huggingface.co/papers/2504.20708", "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* [Dynamic Early Exit in Reasoning Models](https://huggingface.co/papers/2504.15895) (2025)\n* [Leveraging Reasoning Model Answers to Enhance Non-Reasoning Model Capability](https://huggingface.co/papers/2504.09639) (2025)\n* [Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models](https://huggingface.co/papers/2503.16419) (2025)\n* [Reasoning Models Know When They're Right: Probing Hidden States for Self-Verification](https://huggingface.co/papers/2504.05419) (2025)\n* [\"Well, Keep Thinking\": Enhancing LLM Reasoning with Adaptive Injection Decoding](https://huggingface.co/papers/2503.10167) (2025)\n* [Retro-Search: Exploring Untaken Paths for Deeper and Efficient Reasoning](https://huggingface.co/papers/2504.04383) (2025)\n* [Speculative Thinking: Enhancing Small-Model Reasoning with Large Model Guidance at Inference Time](https://huggingface.co/papers/2504.12329) (2025)\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/2504.20966.json

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+{"paper_url": "https://huggingface.co/papers/2504.20966", "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* [BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs](https://huggingface.co/papers/2504.18415) (2025)\n* [Accurate INT8 Training Through Dynamic Block-Level Fallback](https://huggingface.co/papers/2503.08040) (2025)\n* [CASP: Compression of Large Multimodal Models Based on Attention Sparsity](https://huggingface.co/papers/2503.05936) (2025)\n* [RSQ: Learning from Important Tokens Leads to Better Quantized LLMs](https://huggingface.co/papers/2503.01820) (2025)\n* [Using Attention Sinks to Identify and Evaluate Dormant Heads in Pretrained LLMs](https://huggingface.co/papers/2504.03889) (2025)\n* [A Refined Analysis of Massive Activations in LLMs](https://huggingface.co/papers/2503.22329) (2025)\n* [Forgetting Transformer: Softmax Attention with a Forget Gate](https://huggingface.co/papers/2503.02130) (2025)\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/2504.21039.json

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+{"paper_url": "https://huggingface.co/papers/2504.21039", "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* [CyberLLMInstruct: A New Dataset for Analysing Safety of Fine-Tuned LLMs Using Cyber Security Data](https://huggingface.co/papers/2503.09334) (2025)\n* [The Digital Cybersecurity Expert: How Far Have We Come?](https://huggingface.co/papers/2504.11783) (2025)\n* [AttackSeqBench: Benchmarking Large Language Models' Understanding of Sequential Patterns in Cyber Attacks](https://huggingface.co/papers/2503.03170) (2025)\n* [Exploring the Role of Large Language Models in Cybersecurity: A Systematic Survey](https://huggingface.co/papers/2504.15622) (2025)\n* [LLM-Assisted Proactive Threat Intelligence for Automated Reasoning](https://huggingface.co/papers/2504.00428) (2025)\n* [ELTEX: A Framework for Domain-Driven Synthetic Data Generation](https://huggingface.co/papers/2503.15055) (2025)\n* [Secret Breach Detection in Source Code with Large Language Models](https://huggingface.co/papers/2504.18784) (2025)\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/2504.21233.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2504.21233", "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* [Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't](https://huggingface.co/papers/2503.16219) (2025)\n* [How Difficulty-Aware Staged Reinforcement Learning Enhances LLMs' Reasoning Capabilities: A Preliminary Experimental Study](https://huggingface.co/papers/2504.00829) (2025)\n* [Nemotron-CrossThink: Scaling Self-Learning beyond Math Reasoning](https://huggingface.co/papers/2504.13941) (2025)\n* [GRPO-LEAD: A Difficulty-Aware Reinforcement Learning Approach for Concise Mathematical Reasoning in Language Models](https://huggingface.co/papers/2504.09696) (2025)\n* [Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1](https://huggingface.co/papers/2503.24376) (2025)\n* [SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models](https://huggingface.co/papers/2504.11468) (2025)\n* [Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models](https://huggingface.co/papers/2503.16419) (2025)\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/2504.21318.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2504.21318", "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* [Inference-Time Scaling for Complex Tasks: Where We Stand and What Lies Ahead](https://huggingface.co/papers/2504.00294) (2025)\n* [Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn't](https://huggingface.co/papers/2503.16219) (2025)\n* [Nemotron-CrossThink: Scaling Self-Learning beyond Math Reasoning](https://huggingface.co/papers/2504.13941) (2025)\n* [GRPO-LEAD: A Difficulty-Aware Reinforcement Learning Approach for Concise Mathematical Reasoning in Language Models](https://huggingface.co/papers/2504.09696) (2025)\n* [How Difficulty-Aware Staged Reinforcement Learning Enhances LLMs' Reasoning Capabilities: A Preliminary Experimental Study](https://huggingface.co/papers/2504.00829) (2025)\n* [Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model](https://huggingface.co/papers/2503.24290) (2025)\n* [OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement](https://huggingface.co/papers/2503.17352) (2025)\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/2504.21336.json

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+{"paper_url": "https://huggingface.co/papers/2504.21336", "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* [UMIT: Unifying Medical Imaging Tasks via Vision-Language Models](https://huggingface.co/papers/2503.15892) (2025)\n* [Med3DVLM: An Efficient Vision-Language Model for 3D Medical Image Analysis](https://huggingface.co/papers/2503.20047) (2025)\n* [Enhancing SAM with Efficient Prompting and Preference Optimization for Semi-supervised Medical Image Segmentation](https://huggingface.co/papers/2503.04639) (2025)\n* [Enhancing Multi-task Learning Capability of Medical Generalist Foundation Model via Image-centric Multi-annotation Data](https://huggingface.co/papers/2504.09967) (2025)\n* [Foundation Model for Whole-Heart Segmentation: Leveraging Student-Teacher Learning in Multi-Modal Medical Imaging](https://huggingface.co/papers/2503.19005) (2025)\n* [Zeus: Zero-shot LLM Instruction for Union Segmentation in Multimodal Medical Imaging](https://huggingface.co/papers/2504.07336) (2025)\n* [Show and Segment: Universal Medical Image Segmentation via In-Context Learning](https://huggingface.co/papers/2503.19359) (2025)\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/2504.21635.json

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+{"paper_url": "https://huggingface.co/papers/2504.21635", "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* [Low-Resource Transliteration for Roman-Urdu and Urdu Using Transformer-Based Models](https://huggingface.co/papers/2503.21530) (2025)\n* [Kuwain 1.5B: An Arabic SLM via Language Injection](https://huggingface.co/papers/2504.15120) (2025)\n* [Whispering in Amharic: Fine-tuning Whisper for Low-resource Language](https://huggingface.co/papers/2503.18485) (2025)\n* [Command R7B Arabic: A Small, Enterprise Focused, Multilingual, and Culturally Aware Arabic LLM](https://huggingface.co/papers/2503.14603) (2025)\n* [COMI-LINGUA: Expert Annotated Large-Scale Dataset for Multitask NLP in Hindi-English Code-Mixing](https://huggingface.co/papers/2503.21670) (2025)\n* [ARLED: Leveraging LED-based ARMAN Model for Abstractive Summarization of Persian Long Documents](https://huggingface.co/papers/2503.10233) (2025)\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/2504.21776.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2504.21776", "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* [ReaRAG: Knowledge-guided Reasoning Enhances Factuality of Large Reasoning Models with Iterative Retrieval Augmented Generation](https://huggingface.co/papers/2503.21729) (2025)\n* [R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning](https://huggingface.co/papers/2503.05592) (2025)\n* [DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments](https://huggingface.co/papers/2504.03160) (2025)\n* [Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning](https://huggingface.co/papers/2503.09516) (2025)\n* [ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning](https://huggingface.co/papers/2503.19470) (2025)\n* [MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree Search](https://huggingface.co/papers/2503.20757) (2025)\n* [ReTool: Reinforcement Learning for Strategic Tool Use in LLMs](https://huggingface.co/papers/2504.11536) (2025)\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/2504.21850.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2504.21850", "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* [Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs](https://huggingface.co/papers/2504.17432) (2025)\n* [Decoupled Global-Local Alignment for Improving Compositional Understanding](https://huggingface.co/papers/2504.16801) (2025)\n* [MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems](https://huggingface.co/papers/2503.16549) (2025)\n* [Enhancing Compositional Reasoning in Vision-Language Models with Synthetic Preference Data](https://huggingface.co/papers/2504.04740) (2025)\n* [HaploVL: A Single-Transformer Baseline for Multi-Modal Understanding](https://huggingface.co/papers/2503.14694) (2025)\n* [Pixel-SAIL: Single Transformer For Pixel-Grounded Understanding](https://huggingface.co/papers/2504.10465) (2025)\n* [The Scalability of Simplicity: Empirical Analysis of Vision-Language Learning with a Single Transformer](https://huggingface.co/papers/2504.10462) (2025)\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/2504.21855.json

@@ -0,0 +1 @@
+{"paper_url": "https://huggingface.co/papers/2504.21855", "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* [I2V3D: Controllable image-to-video generation with 3D guidance](https://huggingface.co/papers/2503.09733) (2025)\n* [CoGen: 3D Consistent Video Generation via Adaptive Conditioning for Autonomous Driving](https://huggingface.co/papers/2503.22231) (2025)\n* [MagicMotion: Controllable Video Generation with Dense-to-Sparse Trajectory Guidance](https://huggingface.co/papers/2503.16421) (2025)\n* [FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesis](https://huggingface.co/papers/2503.13265) (2025)\n* [EGVD: Event-Guided Video Diffusion Model for Physically Realistic Large-Motion Frame Interpolation](https://huggingface.co/papers/2503.20268) (2025)\n* [VLIPP: Towards Physically Plausible Video Generation with Vision and Language Informed Physical Prior](https://huggingface.co/papers/2503.23368) (2025)\n* [TransAnimate: Taming Layer Diffusion to Generate RGBA Video](https://huggingface.co/papers/2503.17934) (2025)\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`"}