{"total":125,"rows":[{"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":"2503.12605","title":"Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey","created":"2025-03-16","cited_by_count":182,"area":"lr"},{"id":"2503.10631","title":"HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model","created":"2025-03-13","cited_by_count":181,"area":"vla"},{"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":"2508.09987","title":"Echo-4o: Harnessing the Power of GPT-4o Synthetic Images for Improved Image Generation","created":"2025-08-13","cited_by_count":100,"area":null},{"id":"2504.13055","title":"NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation","created":"2025-04-17","cited_by_count":86,"area":"lr"},{"id":"2506.11991","title":"VGR: Visual Grounded Reasoning","created":"2025-06-13","cited_by_count":73,"area":"lr"},{"id":"2505.03733","title":"WebGen-Bench: Evaluating LLMs on Generating Interactive and Functional Websites from Scratch","created":"2025-05-06","cited_by_count":72,"area":"agents"},{"id":"2507.07999","title":"Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Methodology","created":"2025-07-10","cited_by_count":69,"area":null},{"id":"2503.12799","title":"Grounded Chain-of-Thought for Multimodal Large Language Models","created":"2025-03-17","cited_by_count":59,"area":"lr"},{"id":"2510.10689","title":"OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs","created":"2025-10-12","cited_by_count":59,"area":"lr"},{"id":"2510.27492","title":"ThinkMorph: Emergent Properties in Multimodal Interleaved Chain-of-Thought Reasoning","created":"2025-10-30","cited_by_count":56,"area":"lr"},{"id":"2604.05015","title":"Video-MME-v2: Towards the Next Stage in Benchmarks for Comprehensive Video Understanding","created":"2026-04-06","cited_by_count":55,"area":"wm"},{"id":"2506.20430","title":"An Agentic System for Rare Disease Diagnosis with Traceable Reasoning","created":"2025-06-25","cited_by_count":52,"area":"lr"},{"id":"2503.16188","title":"Think or Not Think: A Study of Explicit Thinking in Rule-Based Visual Reinforcement Fine-Tuning","created":"2025-03-20","cited_by_count":44,"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":"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":"2504.07956","title":"VCR-Bench: A Comprehensive Evaluation Framework for Video Chain-of-Thought Reasoning","created":"2025-04-10","cited_by_count":42,"area":"lr"},{"id":"2504.14693","title":"Video-MMLU: A Massive Multi-Discipline Lecture Understanding Benchmark","created":"2025-04-20","cited_by_count":37,"area":null},{"id":"2503.24377","title":"Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models","created":"2025-03-31","cited_by_count":36,"area":"lr"},{"id":"2505.23590","title":"Jigsaw-R1: A Study of Rule-based Visual Reinforcement Learning with Jigsaw Puzzles","created":"2025-05-29","cited_by_count":36,"area":"lr"},{"id":"2505.21327","title":"MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs","created":"2025-05-27","cited_by_count":33,"area":"lr"},{"id":"2505.24718","title":"Reinforcing Video Reasoning with Focused Thinking","created":"2025-05-30","cited_by_count":31,"area":"lr"},{"id":"2503.11557","title":"VERIFY: A Benchmark of Visual Explanation and Reasoning for Investigating Multimodal Reasoning Fidelity","created":"2025-03-14","cited_by_count":23,"area":"lr"},{"id":"2510.10991","title":"A Survey on Agentic Multimodal Large Language Models","created":"2025-10-13","cited_by_count":23,"area":"mllm"},{"id":"2503.10627","title":"SciVerse: Unveiling the Knowledge Comprehension and Visual Reasoning of LMMs on Multi-modal Scientific Problems","created":"2025-03-13","cited_by_count":22,"area":"lr"},{"id":"2503.18071","title":"Mind with Eyes: from Language Reasoning to Multimodal Reasoning","created":"2025-03-23","cited_by_count":22,"area":"lr"},{"id":"2511.15065","title":"Reasoning via Video: The First Evaluation of Video Models' Reasoning Abilities through Maze-Solving Tasks","created":"2025-11-19","cited_by_count":22,"area":"lr"},{"id":"2506.04280","title":"Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark","created":"2025-06-04","cited_by_count":21,"area":"lr"},{"id":"2504.07089","title":"OmniCaptioner: One Captioner to Rule Them All","created":"2025-04-09","cited_by_count":20,"area":null},{"id":"2505.22113","title":"THINK-Bench: Evaluating Thinking Efficiency and Chain-of-Thought Quality of Large Reasoning Models","created":"2025-05-28","cited_by_count":19,"area":"lr"},{"id":"2505.24238","title":"MIRAGE: Assessing Hallucination in Multimodal Reasoning Chains of MLLM","created":"2025-05-30","cited_by_count":17,"area":"lr"},{"id":"2508.09210","title":"MME-Emotion: A Holistic Evaluation Benchmark for Emotional Intelligence in Multimodal Large Language Models","created":"2025-08-11","cited_by_count":17,"area":"mllm"},{"id":"2511.21662","title":"Multi-Crit: Benchmarking Multimodal Judges on Pluralistic Criteria-Following","created":"2025-11-26","cited_by_count":15,"area":"mllm"},{"id":"2505.18536","title":"Reinforcement Fine-Tuning Powers Reasoning Capability of Multimodal Large Language Models","created":"2025-05-24","cited_by_count":14,"area":"lr"},{"id":"2505.18700","title":"GRE Suite: Geo-localization Inference via Fine-Tuned Vision-Language Models and Enhanced Reasoning Chains","created":"2025-05-24","cited_by_count":14,"area":"lr"},{"id":"2505.23522","title":"OmniEarth-Bench: Towards Holistic Evaluation of Earth's Six Spheres and Cross-Spheres Interactions with Multimodal Observational Earth Data","created":"2025-05-29","cited_by_count":14,"area":null},{"id":"2506.23563","title":"MMReason: An Open-Ended Multi-Modal Multi-Step Reasoning Benchmark for MLLMs Toward AGI","created":"2025-06-30","cited_by_count":14,"area":"lr"},{"id":"2504.15780","title":"TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving","created":"2025-04-22","cited_by_count":13,"area":"lr"},{"id":"2512.05112","title":"DraCo: Draft as CoT for Text-to-Image Preview and Rare Concept Generation","created":"2025-12-04","cited_by_count":13,"area":"lr"},{"id":"2505.14404","title":"ViC-Bench: Benchmarking Visual-Interleaved Chain-of-Thought Capability in MLLMs with Free-Style Intermediate State Representations","created":"2025-05-20","cited_by_count":12,"area":"lr"},{"id":"2509.23768","title":"From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning","created":"2025-09-28","cited_by_count":12,"area":"lr"},{"id":"2511.22134","title":"DualVLA: Building a Generalizable Embodied Agent via Partial Decoupling of Reasoning and Action","created":"2025-11-27","cited_by_count":12,"area":"lr"},{"id":"2505.17020","title":"CrossLMM: Decoupling Long Video Sequences from LMMs via Dual Cross-Attention Mechanisms","created":"2025-05-22","cited_by_count":11,"area":"mllm"},{"id":"2509.18639","title":"Understanding-in-Generation: Reinforcing Generative Capability of Unified Model via Infusing Understanding into Generation","created":"2025-09-23","cited_by_count":11,"area":"lr"},{"id":"2602.12506","title":"On Robustness and Chain-of-Thought Consistency of RL-Finetuned VLMs","created":"2026-02-13","cited_by_count":11,"area":"lr"},{"id":"2512.12768","title":"CoRe3D: Collaborative Reasoning as a Foundation for 3D Intelligence","created":"2025-12-14","cited_by_count":10,"area":"mllm"},{"id":"2508.04852","title":"VER-Bench: Evaluating MLLMs on Reasoning with Fine-Grained Visual Evidence","created":"2025-08-06","cited_by_count":9,"area":"lr"},{"id":"2508.08189","title":"Reinforcement Learning for Large Model: A Survey","created":"2025-08-11","cited_by_count":9,"area":"deeprl"},{"id":"2510.09361","title":"BLINK-Twice: You see, but do you observe? A Reasoning Benchmark on Visual Perception","created":"2025-10-10","cited_by_count":9,"area":"lr"},{"id":"2603.02024","title":"MMR-Life: Piecing Together Real-life Scenes for Multimodal Multi-image Reasoning","created":"2026-03-02","cited_by_count":9,"area":"lr"},{"id":"2503.10529","title":"PiSA: A Self-Augmented Data Engine and Training Strategy for 3D Understanding with Large Models","created":"2025-03-13","cited_by_count":8,"area":"mllm"},{"id":"2506.07936","title":"Mimicking or Reasoning: Rethinking Multi-Modal In-Context Learning in Vision-Language Models","created":"2025-06-09","cited_by_count":8,"area":"lr"},{"id":"2509.17040","title":"From Easy to Hard: The MIR Benchmark for Progressive Interleaved Multi-Image Reasoning","created":"2025-09-21","cited_by_count":8,"area":"lr"},{"id":"2509.26636","title":"AccidentBench: Benchmarking Multimodal Understanding and Reasoning in Vehicle Accidents and Beyond","created":"2025-09-30","cited_by_count":8,"area":null},{"id":"2510.08759","title":"Dissecting Embodied Abilities in Multimodal Language Models through Skill-level Evaluation and Diagnosis","created":"2025-10-09","cited_by_count":8,"area":"mllm"},{"id":"2512.19995","title":"Schoenfeld's Anatomy of Mathematical Reasoning by Language Models","created":"2025-12-23","cited_by_count":8,"area":"lr"},{"id":"2601.06993","title":"Can Textual Reasoning Improve the Performance of MLLMs on Fine-grained Visual Classification?","created":"2026-01-11","cited_by_count":8,"area":"lr"},{"id":"2602.07075","title":"LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning","created":"2026-02-06","cited_by_count":8,"area":"lr"},{"id":"2606.06260","title":"OneReason Technical Report","created":"2026-06-04","cited_by_count":8,"area":"lr"},{"id":"2503.21775","title":"StyleMotif: Multi-Modal Motion Stylization using Style-Content Cross Fusion","created":"2025-03-27","cited_by_count":7,"area":"diffusion"},{"id":"2506.19257","title":"MSR-Align: Policy-Grounded Multimodal Alignment for Safety-Aware Reasoning in Vision-Language Models","created":"2025-06-24","cited_by_count":7,"area":"lr"},{"id":"2508.04625","title":"FinMMR: Make Financial Numerical Reasoning More Multimodal, Comprehensive, and Challenging","created":"2025-08-06","cited_by_count":7,"area":"lr"},{"id":"2504.19898","title":"GenCLS++: Pushing the Boundaries of Generative Classification in LLMs Through Comprehensive SFT and RL Studies Across Diverse Datasets","created":"2025-04-28","cited_by_count":6,"area":null},{"id":"2505.16459","title":"MMLU-Reason: Benchmarking Multi-Task Multi-modal Language Understanding and Reasoning","created":"2025-05-22","cited_by_count":6,"area":"lr"},{"id":"2505.22407","title":"Self-Reflective Reinforcement Learning for Diffusion-based Image Reasoning Generation","created":"2025-05-28","cited_by_count":6,"area":"lr"},{"id":"2505.24182","title":"Seeing is Not Reasoning: MVPBench for Graph-based Evaluation of Multi-path Visual Physical CoT","created":"2025-05-30","cited_by_count":6,"area":"lr"},{"id":"2508.13938","title":"MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models","created":"2025-08-19","cited_by_count":6,"area":"mllm"},{"id":"2508.16599","title":"Humans Perceive Wrong Narratives from AI Reasoning Texts","created":"2025-08-09","cited_by_count":6,"area":null},{"id":"2512.10619","title":"DOCR-Inspector: Fine-Grained and Automated Evaluation of Document Parsing with VLM","created":"2025-12-11","cited_by_count":6,"area":null},{"id":"2601.02918","title":"Zoom-IQA: Image Quality Assessment with Reliable Region-Aware Reasoning","created":"2026-01-06","cited_by_count":6,"area":"lr"},{"id":"2601.08758","title":"M3CoTBench: Benchmark Chain-of-Thought of MLLMs in Medical Image Understanding","created":"2026-01-13","cited_by_count":6,"area":"lr"},{"id":"2603.08652","title":"CoCo: Code as CoT for Text-to-Image Preview and Rare Concept Generation","created":"2026-03-09","cited_by_count":6,"area":"lr"},{"id":"2503.06553","title":"ProJudge: A Multi-Modal Multi-Discipline Benchmark and Instruction-Tuning Dataset for MLLM-based Process Judges","created":"2025-03-09","cited_by_count":5,"area":"lr"},{"id":"2506.16796","title":"RealSR-R1: Reinforcement Learning for Real-World Image Super-Resolution with Vision-Language Chain-of-Thought","created":"2025-06-20","cited_by_count":5,"area":"lr"},{"id":"2507.01936","title":"The Thin Line Between Comprehension and Persuasion in LLMs","created":"2025-07-02","cited_by_count":5,"area":null},{"id":"2510.21122","title":"NoisyGRPO: Incentivizing Multimodal CoT Reasoning via Noise Injection and Bayesian Estimation","created":"2025-10-24","cited_by_count":5,"area":"lr"},{"id":"2607.28374","title":"LEDGERMIND: Provenance-Constrained Multimodal Agentic Reasoning with a Structured Evidence Ledger","created":"2026-07-30","cited_by_count":5,"area":"lr"},{"id":"2510.23594","title":"PRISM-Bench: A Benchmark of Puzzle-Based Visual Tasks with CoT Error Detection","created":"2025-10-27","cited_by_count":4,"area":"lr"},{"id":"2512.14944","title":"PuzzleCraft: Exploration-Aware Curriculum Learning for Puzzle-Based RLVR in VLMs","created":"2025-12-16","cited_by_count":4,"area":"lr"},{"id":"2601.05073","title":"Milestones over Outcome: Unlocking Geometric Reasoning with Sub-Goal Verifiable Reward","created":"2026-01-08","cited_by_count":4,"area":"lr"},{"id":"2603.26653","title":"PerceptionComp: A Video Benchmark for Complex Perception-Centric Reasoning","created":"2026-03-27","cited_by_count":4,"area":"lr"},{"id":"2606.02357","title":"Do Multimodal Agents Really Benefit from Tool Use? A Systematic Study of Capability Gains","created":"2026-06-01","cited_by_count":4,"area":null},{"id":"2606.22565","title":"Look Light, Think Heavy: What Multimodal Chain-of-Thought Reasoning Can and Cannot Do","created":"2026-06-21","cited_by_count":4,"area":"lr"},{"id":"2507.20409","title":"Cognitive Chain-of-Thought (CoCoT): Structured Multimodal Reasoning about Social Situations","created":"2025-07-27","cited_by_count":3,"area":"lr"},{"id":"2511.15613","title":"When to Think and When to Look: Uncertainty-Guided Lookback","created":"2025-11-19","cited_by_count":3,"area":"lr"},{"id":"2602.02676","title":"AdaptMMBench: Benchmarking Adaptive Multimodal Reasoning for Mode Selection and Reasoning Process","created":"2026-02-02","cited_by_count":3,"area":"lr"},{"id":"2602.10675","title":"TwiFF (Think With Future Frames): A Large-Scale Dataset for Dynamic Visual Reasoning","created":"2026-02-11","cited_by_count":3,"area":"lr"},{"id":"2603.07078","title":"CoTJudger: A Graph-Driven Framework for Automatic Evaluation of Chain-of-Thought Efficiency and Redundancy in LRMs","created":"2026-03-07","cited_by_count":3,"area":"lr"},{"id":"2605.15198","title":"ATLAS: Agentic or Latent Visual Reasoning? One Word is Enough for Both","created":"2026-05-14","cited_by_count":3,"area":"lr"},{"id":"2606.05966","title":"Causal Scaffolding for Physical Reasoning: A Benchmark for Causally-Informed Physical World Understanding in VLMs","created":"2026-06-04","cited_by_count":3,"area":"lr"},{"id":"2607.02907","title":"ProLaViT: Learning Progressive Latent Visual Thoughts in Structured Latent Space","created":"2026-07-03","cited_by_count":3,"area":"lr"},{"id":"2607.08763","title":"OpenCoF: Learning to Reason Through Video Generation","created":"2026-07-09","cited_by_count":3,"area":"lr"},{"id":"2607.19046","title":"Contrastive On-Policy Distillation","created":"2026-07-21","cited_by_count":3,"area":"distill"},{"id":"2505.16579","title":"Bridging the Dynamic Perception Gap: Training-Free Draft Chain-of-Thought for Dynamic Multimodal Spatial Reasoning","created":"2025-05-22","cited_by_count":2,"area":"lr"},{"id":"2602.13904","title":"Diagnosing Pathological Chain-of-Thought in Reasoning Models","created":"2026-02-14","cited_by_count":2,"area":"lr"},{"id":"2508.04576","title":"ConfProBench: A Confidence Evaluation Benchmark for MLLM-Based Process Judges","created":"2025-08-06","cited_by_count":1,"area":"lr"},{"id":"2509.05542","title":"DreamPRM-1.5: Unlocking the Potential of Each Instance for Multimodal Process Reward Model Training","created":"2025-09-05","cited_by_count":1,"area":"lr"},{"id":"2509.23789","title":"Visual CoT Makes VLMs Smarter but More Fragile","created":"2025-09-28","cited_by_count":1,"area":"lr"},{"id":"2511.00588","title":"Diagnosing Hallucination Risk in AI Surgical Decision-Support: A Sequential Framework for Sequential Validation","created":"2025-11-01","cited_by_count":1,"area":"lr"}],"next_cursor":"100"}