{"total":300,"rows":[{"id":"2508.18265","title":"InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency","created":"2025-08-25","cited_by_count":1510,"area":"lr"},{"id":"2503.06749","title":"Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models","created":"2025-03-09","cited_by_count":665,"area":"lr"},{"id":"2504.07615","title":"VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model","created":"2025-04-10","cited_by_count":526,"area":"lr"},{"id":"2507.01006","title":"GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning","created":"2025-07-01","cited_by_count":466,"area":"lr"},{"id":"2505.14362","title":"DeepEyes: Incentivizing \"Thinking with Images\" via Reinforcement Learning","created":"2025-05-20","cited_by_count":410,"area":"lr"},{"id":"2503.10615","title":"R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization","created":"2025-03-13","cited_by_count":370,"area":"lr"},{"id":"2504.08837","title":"VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning","created":"2025-04-10","cited_by_count":323,"area":"lr"},{"id":"2502.17419","title":"From System 1 to System 2: A Survey of Reasoning Large Language Models","created":"2025-02-24","cited_by_count":320,"area":"lr"},{"id":"2503.07365","title":"MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning","created":"2025-03-10","cited_by_count":303,"area":"lr"},{"id":"2503.12937","title":"R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization","created":"2025-03-17","cited_by_count":301,"area":"lr"},{"id":"2410.19168","title":"MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark","created":"2024-10-24","cited_by_count":288,"area":"lr"},{"id":"2407.01284","title":"We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?","created":"2024-07-01","cited_by_count":286,"area":"lr"},{"id":"2410.07985","title":"Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models","created":"2024-10-10","cited_by_count":284,"area":"lr"},{"id":"2503.07536","title":"LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL","created":"2025-03-10","cited_by_count":248,"area":"lr"},{"id":"2411.10442","title":"Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization","created":"2024-11-15","cited_by_count":239,"area":"lr"},{"id":"2504.11468","title":"SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models","created":"2025-04-10","cited_by_count":212,"area":"lr"},{"id":"2503.12605","title":"Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey","created":"2025-03-16","cited_by_count":182,"area":"lr"},{"id":"2508.11630","title":"Thyme: Think Beyond Images","created":"2025-08-15","cited_by_count":167,"area":"lr"},{"id":"2505.00703","title":"T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT","created":"2025-05-01","cited_by_count":166,"area":"lr"},{"id":"2411.00836","title":"DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models","created":"2024-10-29","cited_by_count":146,"area":"lr"},{"id":"2504.07934","title":"SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement","created":"2025-04-10","cited_by_count":145,"area":"lr"},{"id":"2503.10291","title":"VisualPRM: An Effective Process Reward Model for Multimodal Reasoning","created":"2025-03-13","cited_by_count":139,"area":"lr"},{"id":"2501.05444","title":"Can MLLMs Reason in Multimodality? EMMA: An Enhanced MultiModal ReAsoning Benchmark","created":"2025-01-09","cited_by_count":134,"area":"lr"},{"id":"2406.17294","title":"Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models","created":"2024-06-25","cited_by_count":133,"area":"lr"},{"id":"2412.05237","title":"MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale","created":"2024-12-06","cited_by_count":127,"area":"lr"},{"id":"2508.05629","title":"On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification","created":"2025-08-07","cited_by_count":127,"area":"lr"},{"id":"2502.09621","title":"MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency","created":"2025-02-13","cited_by_count":125,"area":"lr"},{"id":"2506.03569","title":"MiMo-VL Technical Report","created":"2025-06-04","cited_by_count":115,"area":"lr"},{"id":"2406.14852","title":"Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models","created":"2024-06-21","cited_by_count":113,"area":"lr"},{"id":"2407.08739","title":"MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine","created":"2024-07-11","cited_by_count":113,"area":"lr"},{"id":"2508.11737","title":"Ovis2.5 Technical Report","created":"2025-08-15","cited_by_count":108,"area":"lr"},{"id":"2504.15279","title":"VisuLogic: A Benchmark for Evaluating Visual Reasoning in Multi-modal Large Language Models","created":"2025-04-21","cited_by_count":107,"area":"lr"},{"id":"2507.06448","title":"Perception-Aware Policy Optimization for Multimodal Reasoning","created":"2025-07-08","cited_by_count":99,"area":"lr"},{"id":"2508.19652","title":"Self-Rewarding Vision-Language Model via Reasoning Decomposition","created":"2025-08-27","cited_by_count":97,"area":"lr"},{"id":"2504.13055","title":"NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation","created":"2025-04-17","cited_by_count":86,"area":"lr"},{"id":"2505.16839","title":"LaViDa: A Large Diffusion Language Model for Multimodal Understanding","created":"2025-05-22","cited_by_count":84,"area":"lr"},{"id":"2603.11137","title":"Scaling Reasoning Efficiently via Relaxed On-Policy Distillation","created":"2026-03-11","cited_by_count":82,"area":"lr"},{"id":"2501.12368","title":"InternLM-XComposer2.5-Reward: A Simple Yet Effective Multi-Modal Reward Model","created":"2025-01-21","cited_by_count":74,"area":"lr"},{"id":"2406.12753","title":"OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI","created":"2024-06-18","cited_by_count":71,"area":"lr"},{"id":"2409.00147","title":"MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Models","created":"2024-08-30","cited_by_count":70,"area":"lr"},{"id":"2411.00855","title":"Vision-Language Models Can Self-Improve Reasoning via Reflection","created":"2024-10-30","cited_by_count":69,"area":"lr"},{"id":"2501.04686","title":"Unlocking Multimodal Mathematical Reasoning via Process Reward Model","created":"2025-01-08","cited_by_count":65,"area":"lr"},{"id":"2512.03043","title":"OneThinker: All-in-one Reasoning Model for Image and Video","created":"2025-12-02","cited_by_count":56,"area":"lr"},{"id":"2412.11936","title":"A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges","created":"2024-12-16","cited_by_count":55,"area":"lr"},{"id":"2506.04207","title":"Advancing Multimodal Reasoning: From Optimized Cold Start to Staged Reinforcement Learning","created":"2025-06-04","cited_by_count":53,"area":"lr"},{"id":"2408.08640","title":"Math-PUMA: Progressive Upward Multimodal Alignment to Enhance Mathematical Reasoning","created":"2024-08-16","cited_by_count":52,"area":"lr"},{"id":"2502.13260","title":"Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models","created":"2025-02-18","cited_by_count":51,"area":"lr"},{"id":"2411.18203","title":"Critic-V: VLM Critics Help Catch VLM Errors in Multimodal Reasoning","created":"2024-11-27","cited_by_count":50,"area":"lr"},{"id":"2407.08733","title":"Is Your Model Really A Good Math Reasoner? Evaluating Mathematical Reasoning with Checklist","created":"2024-07-11","cited_by_count":48,"area":"lr"},{"id":"2511.15661","title":"VisPlay: Self-Evolving Vision-Language Models from Images","created":"2025-11-19","cited_by_count":47,"area":"lr"},{"id":"2408.15769","title":"A Survey on Evaluation of Multimodal Large Language Models","created":"2024-08-28","cited_by_count":46,"area":"lr"},{"id":"2506.07218","title":"Perception-R1: Advancing Multimodal Reasoning Capabilities of MLLMs via Visual Perception Reward","created":"2025-06-08","cited_by_count":45,"area":"lr"},{"id":"2504.21277","title":"Reinforced MLLM: A Survey on RL-Based Reasoning in Multimodal Large Language Models","created":"2025-04-30","cited_by_count":44,"area":"lr"},{"id":"2507.13348","title":"VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning","created":"2025-07-17","cited_by_count":43,"area":"lr"},{"id":"2510.26802","title":"Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark","created":"2025-10-30","cited_by_count":43,"area":"lr"},{"id":"2412.04447","title":"EgoPlan-Bench2: A Benchmark for Multimodal Large Language Model Planning in Real-World Scenarios","created":"2024-12-05","cited_by_count":41,"area":"lr"},{"id":"2505.05464","title":"Bring Reason to Vision: Understanding Perception and Reasoning through Model Merging","created":"2025-05-08","cited_by_count":40,"area":"lr"},{"id":"2502.13383","title":"MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification","created":"2025-02-19","cited_by_count":39,"area":"lr"},{"id":"2510.09285","title":"Spotlight on Token Perception for Multimodal Reinforcement Learning","created":"2025-10-10","cited_by_count":39,"area":"lr"},{"id":"2410.04509","title":"ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection","created":"2024-10-06","cited_by_count":37,"area":"lr"},{"id":"2511.16334","title":"OpenMMReasoner: Pushing the Frontiers for Multimodal Reasoning with an Open and General Recipe","created":"2025-11-20","cited_by_count":37,"area":"lr"},{"id":"2511.01833","title":"TIR-Bench: A Comprehensive Benchmark for Agentic Thinking-with-Images Reasoning","created":"2025-11-03","cited_by_count":36,"area":"lr"},{"id":"2404.05091","title":"MM-MATH: Advancing Multimodal Math Evaluation with Process Evaluation and Fine-grained Classification","created":"2024-04-07","cited_by_count":35,"area":"lr"},{"id":"2505.19099","title":"SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning","created":"2025-05-25","cited_by_count":34,"area":"lr"},{"id":"2505.20289","title":"VisualToolAgent (VisTA): A Reinforcement Learning Framework for Visual Tool Selection","created":"2025-05-26","cited_by_count":34,"area":"lr"},{"id":"2507.05255","title":"Open Vision Reasoner: Transferring Linguistic Cognitive Behavior for Visual Reasoning","created":"2025-07-07","cited_by_count":34,"area":"lr"},{"id":"2502.02871","title":"Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning","created":"2025-02-05","cited_by_count":33,"area":"lr"},{"id":"2502.20808","title":"MV-MATH: Evaluating Multimodal Math Reasoning in Multi-Visual Contexts","created":"2025-02-28","cited_by_count":32,"area":"lr"},{"id":"2503.13360","title":"Mitigating Visual Forgetting via Take-along Visual Conditioning for Multi-modal Long CoT Reasoning","created":"2025-03-17","cited_by_count":32,"area":"lr"},{"id":"2503.23905","title":"Boosting MLLM Reasoning with Text-Debiased Hint-GRPO","created":"2025-03-31","cited_by_count":32,"area":"lr"},{"id":"2505.13886","title":"Game-RL: Synthesizing Multimodal Verifiable Game Data to Boost VLMs' General Reasoning","created":"2025-05-20","cited_by_count":32,"area":"lr"},{"id":"2409.09039","title":"AutoGeo: Automating Geometric Image Dataset Creation for Enhanced Geometry Understanding","created":"2024-08-28","cited_by_count":29,"area":"lr"},{"id":"2503.13517","title":"CURIE: Evaluating LLMs On Multitask Scientific Long Context Understanding and Reasoning","created":"2025-03-14","cited_by_count":28,"area":"lr"},{"id":"2509.25848","title":"More Thought, Less Accuracy? On the Dual Nature of Reasoning in Vision-Language Models","created":"2025-09-30","cited_by_count":27,"area":"lr"},{"id":"2405.19444","title":"MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions","created":"2024-05-29","cited_by_count":26,"area":"lr"},{"id":"2511.04460","title":"V-Thinker: Interactive Thinking with Images","created":"2025-11-06","cited_by_count":26,"area":"lr"},{"id":"2502.02339","title":"AStar: Boosting Multimodal Reasoning with Automated Structured Thinking","created":"2025-02-04","cited_by_count":25,"area":"lr"},{"id":"2503.24376","title":"Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1","created":"2025-03-31","cited_by_count":25,"area":"lr"},{"id":"2504.12597","title":"GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning","created":"2025-04-17","cited_by_count":25,"area":"lr"},{"id":"2506.10128","title":"ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs","created":"2025-06-11","cited_by_count":25,"area":"lr"},{"id":"2502.16033","title":"Multimodal Inconsistency Reasoning (MMIR): A New Benchmark for Multimodal Reasoning Models","created":"2025-02-22","cited_by_count":24,"area":"lr"},{"id":"2503.18132","title":"MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection","created":"2025-03-23","cited_by_count":24,"area":"lr"},{"id":"2510.11718","title":"CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images","created":"2025-10-13","cited_by_count":23,"area":"lr"},{"id":"2409.13729","title":"MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model","created":"2024-09-10","cited_by_count":21,"area":"lr"},{"id":"2603.09206","title":"MM-Zero: Self-Evolving Multi-Model Vision Language Models From Zero Data","created":"2026-03-10","cited_by_count":21,"area":"lr"},{"id":"2510.05091","title":"Factuality Matters: When Image Generation and Editing Meet Structured Visuals","created":"2025-10-06","cited_by_count":20,"area":"lr"},{"id":"2503.07478","title":"VLRMBench: A Comprehensive and Challenging Benchmark for Vision-Language Reward Models","created":"2025-03-10","cited_by_count":19,"area":"lr"},{"id":"2508.05612","title":"Shuffle-R1: Efficient RL framework for Multimodal Large Language Models via Data-centric Dynamic Shuffle","created":"2025-08-07","cited_by_count":19,"area":"lr"},{"id":"2511.13704","title":"TiViBench: Benchmarking Think-in-Video Reasoning for Video Generative Models","created":"2025-11-17","cited_by_count":19,"area":"lr"},{"id":"2404.14604","title":"Describe-then-Reason: Improving Multimodal Mathematical Reasoning through Visual Comprehension Training","created":"2024-04-22","cited_by_count":17,"area":"lr"},{"id":"2510.08457","title":"ARES: Multimodal Adaptive Reasoning via Difficulty-Aware Token-Level Entropy Shaping","created":"2025-10-09","cited_by_count":17,"area":"lr"},{"id":"2410.12219","title":"OmnixR: Evaluating Omni-modality Language Models on Reasoning across Modalities","created":"2024-10-16","cited_by_count":16,"area":"lr"},{"id":"2501.06430","title":"Open Eyes, Then Reason: Fine-grained Visual Mathematical Understanding in MLLMs","created":"2025-01-11","cited_by_count":16,"area":"lr"},{"id":"2502.15969","title":"Forgotten Polygons: Multimodal Large Language Models are Shape-Blind","created":"2025-02-21","cited_by_count":16,"area":"lr"},{"id":"2503.20271","title":"ViLBench: A Suite for Vision-Language Process Reward Modeling","created":"2025-03-26","cited_by_count":16,"area":"lr"},{"id":"2506.08011","title":"Play to Generalize: Learning to Reason Through Game Play","created":"2025-06-09","cited_by_count":16,"area":"lr"},{"id":"2506.09532","title":"Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models","created":"2025-06-11","cited_by_count":16,"area":"lr"},{"id":"2507.06167","title":"Skywork-R1V3 Technical Report","created":"2025-07-08","cited_by_count":16,"area":"lr"},{"id":"2508.17784","title":"Proximal Supervised Fine-Tuning","created":"2025-08-25","cited_by_count":16,"area":"lr"},{"id":"2505.17534","title":"Co-Reinforcement Learning for Unified Multimodal Understanding and Generation","created":"2025-05-23","cited_by_count":15,"area":"lr"}],"next_cursor":"100"}