{"total":40,"rows":[{"id":"2511.21631","title":"Qwen3-VL Technical Report","created":"2025-11-26","cited_by_count":2793,"area":"mllm"},{"id":"2509.23661","title":"LLaVA-OneVision-1.5: Fully Open Framework for Democratized Multimodal Training","created":"2025-09-28","cited_by_count":244,"area":"mllm"},{"id":"2509.01563","title":"Kwai Keye-VL 1.5 Technical Report","created":"2025-09-01","cited_by_count":73,"area":"mllm"},{"id":"2411.15296","title":"MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs","created":"2024-11-22","cited_by_count":72,"area":"mllm"},{"id":"2507.01949","title":"Kwai Keye-VL Technical Report","created":"2025-07-02","cited_by_count":47,"area":"mllm"},{"id":"2509.25541","title":"Vision-Zero: Scalable VLM Self-Improvement via Strategic Gamified Self-Play","created":"2025-09-29","cited_by_count":37,"area":"mllm"},{"id":"2501.02765","title":"Visual Large Language Models for Generalized and Specialized Applications","created":"2025-01-06","cited_by_count":36,"area":"mllm"},{"id":"2605.21924","title":"Visual-Advantage On-Policy Distillation for Vision-Language Models","created":"2026-05-21","cited_by_count":24,"area":"mllm"},{"id":"2510.10991","title":"A Survey on Agentic Multimodal Large Language Models","created":"2025-10-13","cited_by_count":23,"area":"mllm"},{"id":"2411.01492","title":"EEE-Bench: A Comprehensive Multimodal Electrical And Electronics Engineering Benchmark","created":"2024-11-03","cited_by_count":15,"area":"mllm"},{"id":"2503.16549","title":"MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems","created":"2025-03-19","cited_by_count":10,"area":"mllm"},{"id":"2509.22624","title":"SPARK: Synergistic Policy And Reward Co-Evolving Framework","created":"2025-09-26","cited_by_count":10,"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":"2606.09393","title":"CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning","created":"2026-06-08","cited_by_count":8,"area":"mllm"},{"id":"2604.12358","title":"Why and When Visual Token Pruning Fails? A Study on Relevant Visual Information Shift in MLLMs Decoding","created":"2026-04-14","cited_by_count":7,"area":"mllm"},{"id":"2508.06226","title":"GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines","created":"2025-08-08","cited_by_count":6,"area":"mllm"},{"id":"2603.17508","title":"Omni-I2C: A Holistic Benchmark for High-Fidelity Image-to-Code Generation","created":"2026-03-18","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":"2607.24957","title":"PerceptionBench: Evaluating Atomic Visual Perception in Multimodal Large Language Models","created":"2026-07-27","cited_by_count":4,"area":"mllm"},{"id":"2608.01263","title":"Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models","created":"2026-08-02","cited_by_count":4,"area":"mllm"},{"id":"2510.00063","title":"AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy","created":"2025-09-29","cited_by_count":3,"area":"mllm"},{"id":"2604.03647","title":"Stabilizing Unsupervised Self-Evolution of MLLMs via Continuous Softened Retracing reSampling","created":"2026-04-04","cited_by_count":3,"area":"mllm"},{"id":"2605.26781","title":"LiveK12Bench: Have Large Multimodal Models Truly Conquered High School-level Examinations?","created":"2026-05-26","cited_by_count":3,"area":"mllm"},{"id":"2505.20152","title":"MMGeoLM: Hard Negative Contrastive Learning for Fine-Grained Geometric Understanding in Large Multimodal Models","created":"2025-05-26","cited_by_count":2,"area":"mllm"},{"id":"2602.10815","title":"Why Does RL Generalize Better Than SFT? A Data-Centric Perspective on VLM Post-Training","created":"2026-02-11","cited_by_count":2,"area":"mllm"},{"id":"2412.12606","title":"Multi-Dimensional Insights: Benchmarking Real-World Personalization in Large Multimodal Models","created":"2024-12-17","cited_by_count":1,"area":"mllm"},{"id":"2508.04963","title":"A Metric for MLLM Alignment in Large-scale Recommendation","created":"2025-08-07","cited_by_count":1,"area":"mllm"},{"id":"2512.04032","title":"jina-vlm: Small Multilingual Vision Language Model","created":"2025-12-03","cited_by_count":1,"area":"mllm"},{"id":"2602.08524","title":"GeoFocus: Blending Efficient Global-to-Local Perception for Multimodal Geometry Problem-Solving","created":"2026-02-09","cited_by_count":1,"area":"mllm"},{"id":"2602.22426","title":"SimpleOCR: Rendering Visualized Questions to Teach MLLMs to Read","created":"2026-02-25","cited_by_count":1,"area":"mllm"},{"id":"2512.14735","title":"PyFi: Toward Pyramid-like Financial Image Understanding for VLMs via Adversarial Agents","created":"2025-12-11","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":"2605.07488","title":"Efficient Data Selection for Multimodal Models via Incremental Optimization Utility","created":"2026-05-08","cited_by_count":0,"area":"mllm"},{"id":"2605.30265","title":"LoMo: Local Modality Substitution for Deeper Vision-Language Fusion","created":"2026-05-28","cited_by_count":0,"area":"mllm"},{"id":"2606.16586","title":"LOCUS: Local Visual Cue Search for Enhancing Fine-Grained Perception in Multimodal Large Language Models","created":"2026-06-15","cited_by_count":0,"area":"mllm"},{"id":"2608.04010","title":"ParVL: Parallel Scaling and Expandable Compute Allocation for Multimodal LLMs","created":"2026-08-04","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":"2609.18453","title":"The Mirage of Calibrated Confidence: Trajectory-Independence of Verbalized Confidence in Vision-Language Models","created":"2026-09-16","cited_by_count":0,"area":"mllm"},{"id":"2609.33414","title":"TTRSD: Test-Time Reinforcement Learning with Self-Distillation for Vision-Language Models","created":"2026-09-27","cited_by_count":0,"area":"mllm"},{"id":"2609.34072","title":"PhysFieldBench: Can Multimodal Models Understand Physical Fields?","created":"2026-09-28","cited_by_count":0,"area":"mllm"}],"next_cursor":null}