{"total":86,"rows":[{"id":"2506.08052","title":"ReCogDrive: A Reinforced Cognitive Framework for End-to-End Autonomous Driving","created":"2025-06-09","cited_by_count":198,"area":"mllm"},{"id":"2509.07969","title":"Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search","created":"2025-09-09","cited_by_count":120,"area":"mllm"},{"id":"2605.18740","title":"Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation","created":"2026-05-18","cited_by_count":77,"area":"mllm"},{"id":"2505.02835","title":"R1-Reward: Training Multimodal Reward Model Through Stable Reinforcement Learning","created":"2025-05-05","cited_by_count":65,"area":"mllm"},{"id":"2602.11858","title":"Zooming without Zooming: Region-to-Image Distillation for Fine-Grained Multimodal Perception","created":"2026-02-12","cited_by_count":50,"area":"mllm"},{"id":"2505.23762","title":"ZeroGUI: Automating Online GUI Learning at Zero Human Cost","created":"2025-05-29","cited_by_count":44,"area":"mllm"},{"id":"2506.09049","title":"VIKI-R: Coordinating Embodied Multi-Agent Cooperation via Reinforcement Learning","created":"2025-06-10","cited_by_count":18,"area":"mllm"},{"id":"2506.01274","title":"ReFoCUS: Reinforcement-guided Frame Optimization for Contextual Understanding","created":"2025-06-02","cited_by_count":16,"area":"mllm"},{"id":"2602.06965","title":"MedMO: Grounding and Understanding Multimodal Large Language Model for Medical Images","created":"2026-02-06","cited_by_count":15,"area":"mllm"},{"id":"2509.14033","title":"SAIL-VL2 Technical Report","created":"2025-09-17","cited_by_count":14,"area":"mllm"},{"id":"2607.04884","title":"HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better","created":"2026-07-06","cited_by_count":14,"area":"mllm"},{"id":"2506.18369","title":"RePIC: Reinforced Post-Training for Personalizing Multi-Modal Language Models","created":"2025-06-23","cited_by_count":13,"area":"mllm"},{"id":"2510.24285","title":"ViPER: Empowering the Self-Evolution of Visual Perception Abilities in Vision-Language Model","created":"2025-10-28","cited_by_count":11,"area":"mllm"},{"id":"2511.22055","title":"OralGPT-Omni: A Versatile Dental Multimodal Large Language Model","created":"2025-11-27","cited_by_count":11,"area":"mllm"},{"id":"2510.04039","title":"\\textsc{GUI-Spotlight}: Adaptive Iterative Focus Refinement for Enhanced GUI Visual Grounding","created":"2025-10-05","cited_by_count":10,"area":"mllm"},{"id":"2512.02895","title":"MindGPT-4ov: An Enhanced MLLM via a Multi-Stage Post-Training Paradigm","created":"2025-12-02","cited_by_count":9,"area":"mllm"},{"id":"2512.16909","title":"MomaGraph: State-Aware Unified Scene Graphs with Vision-Language Model for Embodied Task Planning","created":"2025-12-18","cited_by_count":9,"area":"mllm"},{"id":"2602.01334","title":"What Does Vision Tool-Use Reinforcement Learning Really Learn? Disentangling Tool-Induced and Intrinsic Effects for Crop-and-Zoom","created":"2026-02-01","cited_by_count":9,"area":"mllm"},{"id":"2506.07963","title":"SUDER: Self-Improving Unified Large Multimodal Models for Understanding and Generation with Dual Self-Rewards","created":"2025-06-09","cited_by_count":8,"area":"mllm"},{"id":"2510.19307","title":"Unified Reinforcement and Imitation Learning for Vision-Language Models","created":"2025-10-22","cited_by_count":8,"area":"mllm"},{"id":"2512.03963","title":"TempR1: Improving Temporal Understanding of MLLMs via Temporal-Aware Multi-Task Reinforcement Learning","created":"2025-12-03","cited_by_count":8,"area":"mllm"},{"id":"2604.28123","title":"Beyond SFT-to-RL: Pre-alignment via Black-Box On-Policy Distillation for Multimodal RL","created":"2026-04-30","cited_by_count":8,"area":"mllm"},{"id":"2602.23363","title":"MediX-R1: Open Ended Medical Reinforcement Learning","created":"2026-02-26","cited_by_count":7,"area":"mllm"},{"id":"2604.06376","title":"MTA-Agent: An Open Recipe for Multimodal Deep Search Agents","created":"2026-04-07","cited_by_count":7,"area":"mllm"},{"id":"2512.13250","title":"Toward Ambulatory Vision: Learning Visually-Grounded Active View Selection","created":"2025-12-15","cited_by_count":6,"area":"mllm"},{"id":"2602.22932","title":"MSJoE: Jointly Evolving MLLM and Sampler for Efficient Long-Form Video Understanding","created":"2026-02-26","cited_by_count":6,"area":"mllm"},{"id":"2605.20342","title":"ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use in Agentic Video Reinforcement Learning","created":"2026-05-19","cited_by_count":6,"area":"mllm"},{"id":"2510.25801","title":"Metis-SPECS: Decoupling Multimodal Learning via Self-distilled Preference-based Cold Start","created":"2025-10-29","cited_by_count":5,"area":"mllm"},{"id":"2604.05117","title":"Watch Before You Answer: Learning from Visually Grounded Post-Training","created":"2026-04-06","cited_by_count":5,"area":"mllm"},{"id":"2606.20280","title":"ELVA: Exploring Ranking-Driven Universal Multimodal Retrieval","created":"2026-06-18","cited_by_count":5,"area":"mllm"},{"id":"2507.22037","title":"Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security","created":"2025-07-29","cited_by_count":4,"area":"mllm"},{"id":"2512.10691","title":"Enhancing Radiology Report Generation and Visual Grounding using Reinforcement Learning","created":"2025-12-11","cited_by_count":4,"area":"mllm"},{"id":"2512.24271","title":"Taming Hallucinations: Boosting MLLMs' Video Understanding via Counterfactual Video Generation","created":"2025-12-30","cited_by_count":4,"area":"mllm"},{"id":"2605.30794","title":"MechVQA: Benchmarking and Enhancing Multimodal LLMs on Comprehensive Mechanical Drawing Understanding","created":"2026-05-29","cited_by_count":4,"area":"mllm"},{"id":"2605.30912","title":"Attend to Evidence: Evidence-Anchored Spatial Attention Supervision for Multimodal RLVR","created":"2026-05-29","cited_by_count":4,"area":"mllm"},{"id":"2607.23125","title":"Self-Boosting Vision-Language Models with Noisy Student On-Policy Self-Distillation","created":"2026-07-25","cited_by_count":4,"area":"mllm"},{"id":"2510.13108","title":"DriveCritic: Towards Context-Aware, Human-Aligned Evaluation for Autonomous Driving with Vision-Language Models","created":"2025-10-15","cited_by_count":3,"area":"mllm"},{"id":"2512.13043","title":"GTR-Turbo: Merged Checkpoint is Secretly a Free Teacher for Agentic VLM Training","created":"2025-12-15","cited_by_count":3,"area":"mllm"},{"id":"2601.13633","title":"EGM: Efficient Visual Grounding Language Models","created":"2026-01-20","cited_by_count":3,"area":"mllm"},{"id":"2603.00546","title":"Advancing Multimodal Judge Models through a Capability-Oriented Benchmark and MCTS-Driven Data Generation","created":"2026-02-28","cited_by_count":3,"area":"mllm"},{"id":"2604.16243","title":"Find, Fix, Reason: Context Repair for Video Reasoning","created":"2026-04-17","cited_by_count":3,"area":"mllm"},{"id":"2605.09269","title":"DeltaRubric: Generative Multimodal Reward Modeling via Joint Planning and Verification","created":"2026-05-10","cited_by_count":3,"area":"mllm"},{"id":"2606.00579","title":"Sandboxed Coding Agents are Competitive Omni-modal Task Solvers","created":"2026-05-30","cited_by_count":3,"area":"mllm"},{"id":"2505.15963","title":"OViP: Online Vision-Language Preference Learning for VLM Hallucination","created":"2025-05-21","cited_by_count":2,"area":"mllm"},{"id":"2509.15695","title":"ORIC: Benchmarking Object Recognition under Contextual Incongruity in Large Vision-Language Models","created":"2025-09-19","cited_by_count":2,"area":"mllm"},{"id":"2510.16769","title":"See or Say Graphs: Agent-Driven Scalable Graph Structure Understanding with Vision-Language Models","created":"2025-10-19","cited_by_count":2,"area":"mllm"},{"id":"2602.06033","title":"Can Vision Language Models Learn Intuitive Physics from Interaction?","created":"2026-02-05","cited_by_count":2,"area":"mllm"},{"id":"2605.07019","title":"LensVLM: Selective Context Expansion for Compressed Visual Representation of Text","created":"2026-05-07","cited_by_count":2,"area":"mllm"},{"id":"2605.28805","title":"OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration","created":"2026-05-27","cited_by_count":2,"area":"mllm"},{"id":"2607.04364","title":"RL Forgets! Towards Continual Policy Optimization","created":"2026-07-05","cited_by_count":2,"area":"mllm"},{"id":"2607.11175","title":"The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy","created":"2026-07-13","cited_by_count":2,"area":"mllm"},{"id":"2608.09931","title":"Perception Before Supervision: Self-Contained Visual Distillation from Counterfactual Blind Spots","created":"2026-08-10","cited_by_count":2,"area":"mllm"},{"id":"2510.19060","title":"PoSh: Using Scene Graphs To Guide LLMs-as-a-Judge For Detailed Image Descriptions","created":"2025-10-21","cited_by_count":1,"area":"mllm"},{"id":"2512.06726","title":"The Role of Entropy in Visual Grounding: Analysis and Optimization","created":"2025-12-07","cited_by_count":1,"area":"mllm"},{"id":"2601.07516","title":"Controlling Multimodal Conversational Agents with Coverage-Enhanced Latent Actions","created":"2026-01-12","cited_by_count":1,"area":"mllm"},{"id":"2602.10740","title":"Reinforced Curriculum Pre-Alignment for Domain-Adaptive VLMs","created":"2026-02-11","cited_by_count":1,"area":"mllm"},{"id":"2602.22859","title":"From Blind Spots to Gains: Diagnostic-Driven Iterative Training for Large Multimodal Models","created":"2026-02-26","cited_by_count":1,"area":"mllm"},{"id":"2603.05518","title":"CoEditor++: Instruction-based Visual Editing via Cognitive Reasoning","created":"2026-01-31","cited_by_count":1,"area":"mllm"},{"id":"2604.10971","title":"MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models","created":"2026-04-13","cited_by_count":1,"area":"mllm"},{"id":"2605.09422","title":"Perception Without Engagement: Dissecting the Causal Discovery Deficit in LMMs","created":"2026-05-10","cited_by_count":1,"area":"mllm"},{"id":"2605.09996","title":"Omni-Persona: Systematic Benchmarking and Improving Omnimodal Personalization","created":"2026-05-11","cited_by_count":1,"area":"mllm"},{"id":"2609.01409","title":"EdiTikZ: Scientific Figure Editing from Revision Trajectories","created":"2026-09-01","cited_by_count":1,"area":"mllm"},{"id":"2508.17714","title":"F2RVLM: Boosting Fine-grained Fragment Retrieval for Multi-Modal Long-form Dialogue with Vision Language Model","created":"2025-08-25","cited_by_count":0,"area":"mllm"},{"id":"2510.21850","title":"SCoPE VLM: Selective Context Processing for Efficient Document Navigation in Vision-Language Models","created":"2025-10-22","cited_by_count":0,"area":"mllm"},{"id":"2602.11596","title":"MAPLE: Modality-Aware Post-training and Learning Ecosystem","created":"2026-02-12","cited_by_count":0,"area":"mllm"},{"id":"2602.22227","title":"Dynamic Adversarial Reinforcement Learning for Robust Multimodal Large Language Models","created":"2026-01-24","cited_by_count":0,"area":"mllm"},{"id":"2605.01520","title":"MIRL: Mutual Information-Guided Reinforcement Learning for Vision-Language Models","created":"2026-05-02","cited_by_count":0,"area":"mllm"},{"id":"2605.18603","title":"Starve to Perceive: Taming Lazy Perception in VLMs with Constrained Visual Bandwidth","created":"2026-05-18","cited_by_count":0,"area":"mllm"},{"id":"2605.27900","title":"Decoupled Training with Local Reinforcement Fine-Tuning in Federated Learning","created":"2026-05-27","cited_by_count":0,"area":"mllm"},{"id":"2605.28678","title":"DREAM-R: Multimodal Speculative Reasoning with RL-Based Refined Drafting, Precise Verification, and Fully Parallel Execution","created":"2026-05-27","cited_by_count":0,"area":"mllm"},{"id":"2606.11854","title":"Fine-tuning Multi-modal LLMs with ART: Art-based Reinforcement Training","created":"2026-06-10","cited_by_count":0,"area":"mllm"},{"id":"2606.26196","title":"From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models","created":"2026-06-24","cited_by_count":0,"area":"mllm"},{"id":"2607.02490","title":"Visually Grounded Self-Reflection for Vision-Language Models via Reinforcement Learning","created":"2026-07-02","cited_by_count":0,"area":"mllm"},{"id":"2608.07581","title":"Multi-Branch Policy Optimization for Multimodal Large Language Models","created":"2026-08-05","cited_by_count":0,"area":"mllm"},{"id":"2608.18579","title":"MR-IQA-2: Faithful Image Quality Reflection via Fine-Grained Credit Assignment","created":"2026-08-19","cited_by_count":0,"area":"mllm"},{"id":"2608.20122","title":"ArmorOCR: Grounded Adversarial Visual Perception via Observation-Transferred Self-Distillation","created":"2026-08-20","cited_by_count":0,"area":"mllm"},{"id":"2608.21830","title":"Beyond Success and Failure: Length-Aware Contrastive Learning for GUI Agents","created":"2026-08-22","cited_by_count":0,"area":"mllm"},{"id":"2609.22083","title":"MintAct: A Unified Visual Agent for Digital Environments","created":"2026-09-18","cited_by_count":0,"area":"mllm"},{"id":"2609.25891","title":"BAS-OPD: Budget-Aware Selective On-Policy Self-Distillation for Fine-Grained Multimodal Perception","created":"2026-09-22","cited_by_count":0,"area":"mllm"},{"id":"2609.32353","title":"Fewer Tokens, More Self-Teaching: On-Policy Self-Distillation for Extreme Visual Token Reduction","created":"2026-09-26","cited_by_count":0,"area":"mllm"},{"id":"2609.33855","title":"Program-Verified Self-Evolution for Vision-Language Models","created":"2026-09-27","cited_by_count":0,"area":"mllm"},{"id":"2609.35294","title":"Beyond Saying Less: Fine-Grained Alignment for Informative and Faithful Vision-Language Models","created":"2026-09-28","cited_by_count":0,"area":"mllm"},{"id":"2609.36136","title":"Xiaomi-OCR-0 Technical Report","created":"2026-09-28","cited_by_count":0,"area":"mllm"},{"id":"2609.38282","title":"Improving OCR Faithfulness via Gated and Attenuated On-Policy Distillation","created":"2026-09-29","cited_by_count":0,"area":"mllm"},{"id":"2609.38641","title":"Vision-Language-Action Autonomous Driving Agent with Language-based Memory","created":"2026-09-29","cited_by_count":0,"area":"mllm"},{"id":"2610.13465","title":"When MLLMs miss what humans read: diagnosing and learning to read squint text","created":"2026-10-09","cited_by_count":0,"area":"mllm"}],"next_cursor":null}