{"total":104,"rows":[{"id":"2409.12191","title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution","created":"2024-09-18","cited_by_count":4234,"area":"mllm"},{"id":"2503.01743","title":"Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs","created":"2025-03-03","cited_by_count":521,"area":"mllm"},{"id":"2406.18521","title":"CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs","created":"2024-06-26","cited_by_count":234,"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":"2402.12451","title":"The Revolution of Multimodal Large Language Models: A Survey","created":"2024-02-19","cited_by_count":137,"area":"mllm"},{"id":"2412.07755","title":"SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models","created":"2024-12-10","cited_by_count":114,"area":"mllm"},{"id":"2408.03361","title":"GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI","created":"2024-08-06","cited_by_count":96,"area":"mllm"},{"id":"2501.06598","title":"ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code Generation","created":"2025-01-11","cited_by_count":92,"area":"mllm"},{"id":"2403.20213","title":"VHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis","created":"2024-03-29","cited_by_count":86,"area":"mllm"},{"id":"2412.12075","title":"CG-Bench: Clue-grounded Question Answering Benchmark for Long Video Understanding","created":"2024-12-16","cited_by_count":85,"area":"mllm"},{"id":"2412.02210","title":"CC-OCR: A Comprehensive and Challenging OCR Benchmark for Evaluating Large Multimodal Models in Literacy","created":"2024-12-03","cited_by_count":81,"area":"mllm"},{"id":"2409.20566","title":"MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning","created":"2024-09-30","cited_by_count":76,"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":"2411.10803","title":"Multi-Stage Vision Token Dropping: Towards Efficient Multimodal Large Language Model","created":"2024-11-16","cited_by_count":68,"area":"mllm"},{"id":"2502.14881","title":"A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations","created":"2025-02-14","cited_by_count":67,"area":"mllm"},{"id":"2410.16153","title":"Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages","created":"2024-10-21","cited_by_count":64,"area":"mllm"},{"id":"2509.15221","title":"ScaleCUA: Scaling Open-Source Computer Use Agents with Cross-Platform Data","created":"2025-09-18","cited_by_count":60,"area":"mllm"},{"id":"2501.13925","title":"GeoPixel: Pixel Grounding Large Multimodal Model in Remote Sensing","created":"2025-01-23","cited_by_count":57,"area":"mllm"},{"id":"2406.07057","title":"MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models","created":"2024-06-11","cited_by_count":53,"area":"mllm"},{"id":"2411.09968","title":"Seeing Clearly by Layer Two: Enhancing Attention Heads to Alleviate Hallucination in LVLMs","created":"2024-11-15","cited_by_count":52,"area":"mllm"},{"id":"2410.09732","title":"LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models","created":"2024-10-13","cited_by_count":51,"area":"mllm"},{"id":"2402.12501","title":"Your Vision-Language Model Itself Is a Strong Filter: Towards High-Quality Instruction Tuning with Data Selection","created":"2024-02-19","cited_by_count":48,"area":"mllm"},{"id":"2403.15637","title":"CoNVOI: Context-aware Navigation using Vision Language Models in Outdoor and Indoor Environments","created":"2024-03-22","cited_by_count":43,"area":"mllm"},{"id":"2410.09874","title":"ImagineNav: Prompting Vision-Language Models as Embodied Navigator through Scene Imagination","created":"2024-10-13","cited_by_count":38,"area":"mllm"},{"id":"2501.02268","title":"What Kind of Visual Tokens Do We Need? Training-free Visual Token Pruning for Multi-modal Large Language Models from the Perspective of Graph","created":"2025-01-04","cited_by_count":36,"area":"mllm"},{"id":"2406.10900","title":"AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models","created":"2024-06-16","cited_by_count":32,"area":"mllm"},{"id":"2406.16442","title":"EmoLLM: Multimodal Emotional Understanding Meets Large Language Models","created":"2024-06-24","cited_by_count":31,"area":"mllm"},{"id":"2402.06599","title":"On the Out-Of-Distribution Generalization of Multimodal Large Language Models","created":"2024-02-09","cited_by_count":30,"area":"mllm"},{"id":"2407.15211","title":"Failures to Find Transferable Image Jailbreaks Between Vision-Language Models","created":"2024-07-21","cited_by_count":30,"area":"mllm"},{"id":"2501.03225","title":"Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation","created":"2025-01-06","cited_by_count":30,"area":"mllm"},{"id":"2502.13146","title":"Re-Align: Aligning Vision Language Models via Retrieval-Augmented Direct Preference Optimization","created":"2025-02-18","cited_by_count":29,"area":"mllm"},{"id":"2604.07429","title":"GameWorld: Towards Standardized and Verifiable Evaluation of Multimodal Game Agents","created":"2026-04-08","cited_by_count":28,"area":"mllm"},{"id":"2406.14194","title":"VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model","created":"2024-06-20","cited_by_count":26,"area":"mllm"},{"id":"2412.05819","title":"[CLS] Token Tells Everything Needed for Training-free Efficient MLLMs","created":"2024-12-08","cited_by_count":26,"area":"mllm"},{"id":"2411.09301","title":"LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language Interpretation","created":"2024-11-14","cited_by_count":25,"area":"mllm"},{"id":"2404.03118","title":"LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models","created":"2024-04-03","cited_by_count":24,"area":"mllm"},{"id":"2412.02573","title":"Remote Sensing SpatioTemporal Vision-Language Models: A Comprehensive Survey","created":"2024-12-03","cited_by_count":23,"area":"mllm"},{"id":"2412.03665","title":"Personalizing Multimodal Large Language Models for Image Captioning: An Experimental Analysis","created":"2024-12-04","cited_by_count":23,"area":"mllm"},{"id":"2412.20105","title":"ST$^3$: Accelerating Multimodal Large Language Model by Spatial-Temporal Visual Token Trimming","created":"2024-12-28","cited_by_count":20,"area":"mllm"},{"id":"2510.08510","title":"To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models","created":"2025-10-09","cited_by_count":20,"area":"mllm"},{"id":"2401.15071","title":"From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities","created":"2024-01-26","cited_by_count":19,"area":"mllm"},{"id":"2509.22646","title":"Learning Human-Perceived Fakeness in AI-Generated Videos via Multimodal LLMs","created":"2025-09-26","cited_by_count":17,"area":"mllm"},{"id":"2410.14170","title":"Personalized Image Generation with Large Multimodal Models","created":"2024-10-18","cited_by_count":15,"area":"mllm"},{"id":"2408.04868","title":"ChatGPT Meets Iris Biometrics","created":"2024-08-09","cited_by_count":14,"area":"mllm"},{"id":"2602.09973","title":"RoboInter: A Holistic Intermediate Representation Suite Towards Robotic Manipulation","created":"2026-02-10","cited_by_count":14,"area":"mllm"},{"id":"2412.08737","title":"Euclid: Supercharging Multimodal LLMs with Synthetic High-Fidelity Visual Descriptions","created":"2024-12-11","cited_by_count":13,"area":"mllm"},{"id":"2312.15011","title":"Gemini vs GPT-4V: A Preliminary Comparison and Combination of Vision-Language Models Through Qualitative Cases","created":"2023-12-22","cited_by_count":12,"area":"mllm"},{"id":"2501.04322","title":"Eve: Efficient Multimodal Vision Language Models with Elastic Visual Experts","created":"2025-01-08","cited_by_count":11,"area":"mllm"},{"id":"2601.16973","title":"VisGym: Diverse, Customizable, Scalable Environments for Multimodal Agents","created":"2026-01-23","cited_by_count":11,"area":"mllm"},{"id":"2408.16176","title":"VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images","created":"2024-08-28","cited_by_count":10,"area":"mllm"},{"id":"2411.14164","title":"FoPru: Focal Pruning for Efficient Large Vision-Language Models","created":"2024-11-21","cited_by_count":10,"area":"mllm"},{"id":"2412.01822","title":"VLsI: Verbalized Layers-to-Interactions from Large to Small Vision Language Models","created":"2024-12-02","cited_by_count":10,"area":"mllm"},{"id":"2503.16585","title":"Distributed LLMs and Multimodal Large Language Models: A Survey on Advances, Challenges, and Future Directions","created":"2025-03-20","cited_by_count":10,"area":"mllm"},{"id":"2410.02745","title":"AVG-LLaVA: An Efficient Large Multimodal Model with Adaptive Visual Granularity","created":"2024-09-20","cited_by_count":9,"area":"mllm"},{"id":"2503.01887","title":"When Continue Learning Meets Multimodal Large Language Model: A Survey","created":"2025-02-27","cited_by_count":9,"area":"mllm"},{"id":"2404.17912","title":"SERPENT-VLM : Self-Refining Radiology Report Generation Using Vision Language Models","created":"2024-04-27","cited_by_count":8,"area":"mllm"},{"id":"2405.10311","title":"UniRAG: Universal Retrieval Augmentation for Large Vision Language Models","created":"2024-05-16","cited_by_count":8,"area":"mllm"},{"id":"2405.17821","title":"RITUAL: Random Image Transformations as a Universal Anti-hallucination Lever in Large Vision Language Models","created":"2024-05-28","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":"2512.20168","title":"Odysseus: Jailbreaking Commercial Multimodal LLM-integrated Systems via Dual Steganography","created":"2025-12-23","cited_by_count":8,"area":"mllm"},{"id":"2403.10492","title":"Mitigating Dialogue Hallucination for Large Vision Language Models via Adversarial Instruction Tuning","created":"2024-03-15","cited_by_count":7,"area":"mllm"},{"id":"2412.18072","title":"MMFactory: A Universal Solution Search Engine for Vision-Language Tasks","created":"2024-12-24","cited_by_count":7,"area":"mllm"},{"id":"2501.15046","title":"Evaluating Hallucination in Large Vision-Language Models based on Context-Aware Object Similarities","created":"2025-01-25","cited_by_count":7,"area":"mllm"},{"id":"2407.05758","title":"Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports","created":"2024-07-08","cited_by_count":6,"area":"mllm"},{"id":"2411.19103","title":"VARCO-VISION: Expanding Frontiers in Korean Vision-Language Models","created":"2024-11-28","cited_by_count":6,"area":"mllm"},{"id":"2410.06456","title":"From Generalist to Specialist: Adapting Vision Language Models via Task-Specific Visual Instruction Tuning","created":"2024-10-09","cited_by_count":5,"area":"mllm"},{"id":"2509.17481","title":"ChartHal: A Fine-grained Framework Evaluating Hallucination of Large Vision Language Models in Chart Understanding","created":"2025-09-22","cited_by_count":5,"area":"mllm"},{"id":"2407.12064","title":"LiteGPT: Large Vision-Language Model for Joint Chest X-ray Localization and Classification Task","created":"2024-07-16","cited_by_count":4,"area":"mllm"},{"id":"2407.15819","title":"Accelerating Pre-training of Multimodal LLMs via Chain-of-Sight","created":"2024-07-22","cited_by_count":4,"area":"mllm"},{"id":"2410.01438","title":"The Great Contradiction Showdown: How Jailbreak and Stealth Wrestle in Vision-Language Models?","created":"2024-10-02","cited_by_count":4,"area":"mllm"},{"id":"2410.24148","title":"Exploring Vision Language Models for Facial Attribute Recognition: Emotion, Race, Gender, and Age","created":"2024-10-31","cited_by_count":4,"area":"mllm"},{"id":"2504.06838","title":"ZIP: An Efficient Zeroth-order Prompt Tuning for Black-box Vision-Language Models","created":"2025-04-09","cited_by_count":4,"area":"mllm"},{"id":"2507.08982","title":"VIP: Visual Information Protection through Adversarial Attacks on Vision-Language Models","created":"2025-07-11","cited_by_count":4,"area":"mllm"},{"id":"2509.08490","title":"A Structured Review of Underwater Object Detection Challenges and Solutions: From Traditional to Large Vision Language Models","created":"2025-09-10","cited_by_count":4,"area":"mllm"},{"id":"2510.11496","title":"AndesVL Technical Report: An Efficient Mobile-side Multimodal Large Language Model","created":"2025-10-13","cited_by_count":4,"area":"mllm"},{"id":"2511.14900","title":"Skin-R1: Clinical Knowledge-Guided Dermatological Diagnosis Using Vision-Language Models","created":"2025-11-18","cited_by_count":4,"area":"mllm"},{"id":"2603.04846","title":"Multi-Paradigm Collaborative Adversarial Attack Against Multi-Modal Large Language Models","created":"2026-03-05","cited_by_count":4,"area":"mllm"},{"id":"2605.12684","title":"Visual Aesthetic Benchmark: Can Frontier Models Judge Beauty?","created":"2026-05-12","cited_by_count":4,"area":"mllm"},{"id":"2606.23888","title":"E-MRL: Cross-view Aligned Evidence-driven Multimodal Reinforcement Learning for Reliable 3D Tumor Analysis","created":"2026-06-22","cited_by_count":4,"area":"mllm"},{"id":"2409.10994","title":"Less is More: A Simple yet Effective Token Reduction Method for Efficient Multi-modal LLMs","created":"2024-09-17","cited_by_count":3,"area":"mllm"},{"id":"2508.10667","title":"AddressVLM: Cross-view Alignment Tuning for Image Address Localization using Large Vision-Language Models","created":"2025-08-14","cited_by_count":3,"area":"mllm"},{"id":"2402.14492","title":"Towards Robust Instruction Tuning on Multimodal Large Language Models","created":"2024-02-22","cited_by_count":2,"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":"2508.17860","title":"AVAM: Universal Training-free Adaptive Visual Anchoring Embedded into Multimodal Large Language Model for Multi-image Question Answering","created":"2025-08-25","cited_by_count":2,"area":"mllm"},{"id":"2602.04657","title":"TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models","created":"2026-02-04","cited_by_count":2,"area":"mllm"},{"id":"2411.06287","title":"Hidden in Plain Sight: Evaluating Abstract Shape Recognition in Vision-Language Models","created":"2024-11-09","cited_by_count":1,"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":"2506.08283","title":"Serendipitous Recommendation with Multimodal LLM","created":"2025-06-09","cited_by_count":1,"area":"mllm"},{"id":"2509.17425","title":"Evaluating Multimodal Large Language Models with Daily Composite Tasks in Home Environments","created":"2025-09-22","cited_by_count":1,"area":"mllm"},{"id":"2602.10799","title":"RSHallu: Dual-Mode Hallucination Evaluation for Remote-Sensing Multimodal Large Language Models with Domain-Tailored Mitigation","created":"2026-02-11","cited_by_count":1,"area":"mllm"},{"id":"2603.22763","title":"ENC-Bench: A Benchmark for Evaluating Multimodal Large Language Models in Electronic Navigational Chart Understanding","created":"2026-03-24","cited_by_count":1,"area":"mllm"},{"id":"2604.07753","title":"Symbiotic-MoE: Unlocking the Synergy between Generation and Understanding","created":"2026-04-09","cited_by_count":1,"area":"mllm"},{"id":"2608.10489","title":"When Vision Becomes Text: Visual Token Pruning via Cross-Modal Residual Guidance in VLMs","created":"2026-08-11","cited_by_count":1,"area":"mllm"},{"id":"2410.21480","title":"AiSciVision: A Framework for Specializing Large Multimodal Models in Scientific Image Classification","created":"2024-10-28","cited_by_count":0,"area":"mllm"},{"id":"2508.05053","title":"Finding Needles in Images: Can Multimodal LLMs Locate Fine Details?","created":"2025-08-07","cited_by_count":0,"area":"mllm"},{"id":"2511.13420","title":"VOPE: Revisiting Hallucination of Vision-Language Models in Voluntary Imagination Task","created":"2025-11-17","cited_by_count":0,"area":"mllm"},{"id":"2603.08497","title":"Reading $\\neq$ Seeing: Diagnosing and Closing the Typography Gap in Vision-Language Models","created":"2026-03-09","cited_by_count":0,"area":"mllm"},{"id":"2605.09338","title":"A General Framework for Multimodal LLM-Based Multimedia Understanding in Large-Scale Recommendation Systems","created":"2026-05-10","cited_by_count":0,"area":"mllm"},{"id":"2605.15711","title":"EntropyScan: Towards Model-level Backdoor Detection in LVLMs via Visual Attention Entropy","created":"2026-05-15","cited_by_count":0,"area":"mllm"},{"id":"2605.21625","title":"Flat-Pack Bench: Evaluating Spatio-Temporal Understanding in Large Vision-Language Models through Furniture Assembly","created":"2026-05-20","cited_by_count":0,"area":"mllm"}],"next_cursor":"100"}