{"total":46,"rows":[{"id":"2410.17247","title":"PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction","created":"2024-10-22","cited_by_count":294,"area":"mllm"},{"id":"2408.04840","title":"mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models","created":"2024-08-09","cited_by_count":291,"area":"mllm"},{"id":"2505.20275","title":"ImgEdit: A Unified Image Editing Dataset and Benchmark","created":"2025-05-26","cited_by_count":231,"area":"mllm"},{"id":"2409.14485","title":"Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding","created":"2024-09-22","cited_by_count":213,"area":"mllm"},{"id":"2407.03320","title":"InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output","created":"2024-07-03","cited_by_count":195,"area":"mllm"},{"id":"2502.04326","title":"WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs","created":"2025-02-06","cited_by_count":155,"area":"mllm"},{"id":"2408.08872","title":"xGen-MM (BLIP-3): A Family of Open Large Multimodal Models","created":"2024-08-16","cited_by_count":116,"area":"mllm"},{"id":"2506.10967","title":"Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs","created":"2025-06-12","cited_by_count":96,"area":"mllm"},{"id":"2501.07888","title":"Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding","created":"2025-01-14","cited_by_count":81,"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":"2501.14818","title":"Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models","created":"2025-01-20","cited_by_count":70,"area":"mllm"},{"id":"2504.07957","title":"MM-IFEngine: Towards Multimodal Instruction Following","created":"2025-04-10","cited_by_count":42,"area":"mllm"},{"id":"2410.17637","title":"MIA-DPO: Multi-Image Augmented Direct Preference Optimization For Large Vision-Language Models","created":"2024-10-23","cited_by_count":34,"area":"mllm"},{"id":"2504.10068","title":"Mavors: Multi-granularity Video Representation for Multimodal Large Language Model","created":"2025-04-14","cited_by_count":32,"area":"mllm"},{"id":"2502.11903","title":"MMRC: A Large-Scale Benchmark for Understanding Multimodal Large Language Model in Real-World Conversation","created":"2025-02-17","cited_by_count":29,"area":"mllm"},{"id":"2605.27365","title":"LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding","created":"2026-05-26","cited_by_count":28,"area":"mllm"},{"id":"2511.16672","title":"EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards","created":"2025-11-20","cited_by_count":27,"area":"mllm"},{"id":"2412.09613","title":"PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models","created":"2024-12-12","cited_by_count":25,"area":"mllm"},{"id":"2503.02358","title":"Are Large Vision Language Models Good Game Players?","created":"2025-03-04","cited_by_count":19,"area":"mllm"},{"id":"2507.14675","title":"Docopilot: Improving Multimodal Models for Document-Level Understanding","created":"2025-07-19","cited_by_count":19,"area":"mllm"},{"id":"2412.16158","title":"HoVLE: Unleashing the Power of Monolithic Vision-Language Models with Holistic Vision-Language Embedding","created":"2024-12-20","cited_by_count":10,"area":"mllm"},{"id":"2502.01960","title":"MPIC: Position-Independent Multimodal Context Caching System for Efficient MLLM Serving","created":"2025-02-04","cited_by_count":8,"area":"mllm"},{"id":"2505.19031","title":"Medical Large Vision Language Models with Multi-Image Visual Ability","created":"2025-05-25","cited_by_count":8,"area":"mllm"},{"id":"2505.24449","title":"When Large Multimodal Models Confront Evolving Knowledge: Challenges and Explorations","created":"2025-05-30","cited_by_count":7,"area":"mllm"},{"id":"2503.07002","title":"Taking Notes Brings Focus? Towards Multi-Turn Multimodal Dialogue Learning","created":"2025-03-10","cited_by_count":5,"area":"mllm"},{"id":"2411.14062","title":"MMGenBench: Fully Automatically Evaluating LMMs from the Text-to-Image Generation Perspective","created":"2024-11-21","cited_by_count":4,"area":"mllm"},{"id":"2503.18484","title":"Benchmarking and Boosting Multilingual Capabilities of LVLMs via OCR-Centric Reinforcement Learning","created":"2025-03-24","cited_by_count":4,"area":"mllm"},{"id":"2505.09498","title":"Flash-VL 2B: Optimizing Vision-Language Model Performance for Ultra-Low Latency and High Throughput","created":"2025-05-14","cited_by_count":4,"area":"mllm"},{"id":"2506.06279","title":"CoMemo: LVLMs Need Image Context with Image Memory","created":"2025-06-06","cited_by_count":4,"area":"mllm"},{"id":"2412.12735","title":"GIRAFFE: Design Choices for Extending the Context Length of Visual Language Models","created":"2024-12-17","cited_by_count":2,"area":"mllm"},{"id":"2505.10541","title":"Exploring Implicit Visual Misunderstandings in Multimodal Large Language Models through Attention Analysis","created":"2025-05-15","cited_by_count":2,"area":"mllm"},{"id":"2505.22396","title":"Zooming from Context to Cue: Hierarchical Preference Optimization for Multi-Image MLLMs","created":"2025-05-28","cited_by_count":2,"area":"mllm"},{"id":"2602.15927","title":"Visual Memory Injection Attacks for Multi-Turn Conversations","created":"2026-02-17","cited_by_count":2,"area":"mllm"},{"id":"2602.18884","title":"TPRU: Advancing Temporal and Procedural Understanding in Large Multimodal Models","created":"2026-02-21","cited_by_count":2,"area":"mllm"},{"id":"2603.07048","title":"Looking Back and Forth: Cross-Image Attention Calibration and Attentive Preference Learning for Multi-Image Hallucination Mitigation","created":"2026-03-07","cited_by_count":2,"area":"mllm"},{"id":"2509.25896","title":"LLaVAShield: Safeguarding Multimodal Multi-Turn Dialogues in Vision-Language Models","created":"2025-09-30","cited_by_count":1,"area":"mllm"},{"id":"2510.15317","title":"VERITAS: Leveraging Vision Priors and Expert Fusion to Improve Multimodal Data","created":"2025-10-17","cited_by_count":0,"area":"mllm"},{"id":"2510.19316","title":"KORE: Enhancing Knowledge Injection for Large Multimodal Models via Knowledge-Oriented Controls","created":"2025-10-22","cited_by_count":0,"area":"mllm"},{"id":"2602.21854","title":"FewMMBench: A Benchmark for Multimodal Few-Shot Learning","created":"2026-02-25","cited_by_count":0,"area":"mllm"},{"id":"2604.16502","title":"Topology-Aware Layer Pruning for Large Vision-Language Models","created":"2026-04-14","cited_by_count":0,"area":"mllm"},{"id":"2605.29535","title":"AsymVLM: Asymmetric Token Pruning for Efficient Vision-Language Model Inference","created":"2026-05-28","cited_by_count":0,"area":"mllm"},{"id":"2606.19338","title":"Beyond the Current Observation: Evaluating Multimodal Large Language Models in Controllable Non-Markov Games","created":"2026-06-17","cited_by_count":0,"area":"mllm"},{"id":"2607.14499","title":"Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn Interactions","created":"2026-07-16","cited_by_count":0,"area":"mllm"},{"id":"2608.30653","title":"Fine-Grained Multi Image Object Hallucination Benchmark","created":"2026-08-31","cited_by_count":0,"area":"mllm"},{"id":"2609.38368","title":"Composition, Not Conversation: VLMs Lose the Scene, Not the Thread","created":"2026-09-29","cited_by_count":0,"area":"mllm"},{"id":"2610.05940","title":"ReMem: Streaming Video Understanding With Long Context Retention","created":"2026-10-05","cited_by_count":0,"area":"mllm"}],"next_cursor":null}