{"total":82,"rows":[{"id":"2502.09560","title":"EmbodiedBench: Comprehensive Benchmarking Multi-modal Large Language Models for Vision-Driven Embodied Agents","created":"2025-02-13","cited_by_count":221,"area":"mllm"},{"id":"2501.01957","title":"VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction","created":"2025-01-03","cited_by_count":197,"area":"mllm"},{"id":"2501.00321","title":"OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning","created":"2024-12-31","cited_by_count":173,"area":"mllm"},{"id":"2510.12801","title":"DeepMMSearch-R1: Empowering Multimodal LLMs in Multimodal Web Search","created":"2025-10-14","cited_by_count":42,"area":"mllm"},{"id":"2502.05177","title":"Long-VITA: Scaling Large Multi-modal Models to 1 Million Tokens with Leading Short-Context Accuracy","created":"2025-02-07","cited_by_count":39,"area":"mllm"},{"id":"2503.06486","title":"PerturboLLaVA: Reducing Multimodal Hallucinations with Perturbative Visual Training","created":"2025-03-09","cited_by_count":38,"area":"mllm"},{"id":"2503.10621","title":"DriveLMM-o1: A Step-by-Step Reasoning Dataset and Large Multimodal Model for Driving Scenario Understanding","created":"2025-03-13","cited_by_count":36,"area":"mllm"},{"id":"2406.02539","title":"Parrot: Multilingual Visual Instruction Tuning","created":"2024-06-04","cited_by_count":30,"area":"mllm"},{"id":"2406.10638","title":"Unveiling the Ignorance of MLLMs: Seeing Clearly, Answering Incorrectly","created":"2024-06-15","cited_by_count":30,"area":"mllm"},{"id":"2505.10610","title":"MMLongBench: Benchmarking Long-Context Vision-Language Models Effectively and Thoroughly","created":"2025-05-15","cited_by_count":29,"area":"mllm"},{"id":"2506.21356","title":"ShotBench: Expert-Level Cinematic Understanding in Vision-Language Models","created":"2025-06-26","cited_by_count":22,"area":"mllm"},{"id":"2501.05901","title":"Valley2: Exploring Multimodal Models with Scalable Vision-Language Design","created":"2025-01-10","cited_by_count":21,"area":"mllm"},{"id":"2506.05344","title":"SparseMM: Head Sparsity Emerges from Visual Concept Responses in MLLMs","created":"2025-06-05","cited_by_count":20,"area":"mllm"},{"id":"2410.00296","title":"VLMGuard: Bootstrapping Malicious Prompt Detectors from Unlabeled Vision-Language Prompts in the Wild","created":"2024-10-01","cited_by_count":18,"area":"mllm"},{"id":"2409.04828","title":"POINTS: Improving Your Vision-language Model with Affordable Strategies","created":"2024-09-07","cited_by_count":17,"area":"mllm"},{"id":"2505.19028","title":"InfoChartQA: A Benchmark for Multimodal Question Answering on Infographic Charts","created":"2025-05-25","cited_by_count":17,"area":"mllm"},{"id":"2504.15280","title":"Seeing from Another Perspective: Evaluating Multi-View Understanding in MLLMs","created":"2025-04-21","cited_by_count":16,"area":"mllm"},{"id":"2503.02304","title":"A Token-level Text Image Foundation Model for Document Understanding","created":"2025-03-04","cited_by_count":14,"area":"mllm"},{"id":"2503.23573","title":"DASH: Detection and Assessment of Systematic Hallucinations of VLMs","created":"2025-03-30","cited_by_count":14,"area":"mllm"},{"id":"2505.16416","title":"Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Large Vision-Language Models","created":"2025-05-22","cited_by_count":14,"area":"mllm"},{"id":"2509.21789","title":"Visual Multi-Agent System: Mitigating Hallucination Snowballing via Visual Flow","created":"2025-09-26","cited_by_count":13,"area":"mllm"},{"id":"2412.08443","title":"POINTS1.5: Building a Vision-Language Model towards Real World Applications","created":"2024-12-11","cited_by_count":12,"area":"mllm"},{"id":"2503.21817","title":"Skip-Vision: Efficient and Scalable Acceleration of Vision-Language Models via Adaptive Token Skipping","created":"2025-03-26","cited_by_count":12,"area":"mllm"},{"id":"2506.05551","title":"When Semantics Mislead Vision: Mitigating Large Multimodal Models Hallucinations in Scene Text Spotting and Understanding","created":"2025-06-05","cited_by_count":12,"area":"mllm"},{"id":"2412.00142","title":"Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features","created":"2024-11-28","cited_by_count":11,"area":"mllm"},{"id":"2412.05983","title":"Chimera: Improving Generalist Model with Domain-Specific Experts","created":"2024-12-08","cited_by_count":11,"area":"mllm"},{"id":"2503.19404","title":"LangBridge: Interpreting Image as a Combination of Language Embeddings","created":"2025-03-25","cited_by_count":10,"area":"mllm"},{"id":"2506.15681","title":"GenRecal: Generation after Recalibration from Large to Small Vision-Language Models","created":"2025-06-18","cited_by_count":10,"area":"mllm"},{"id":"2508.05580","title":"Follow-Your-Instruction: A Comprehensive MLLM Agent for World Data Synthesis","created":"2025-08-07","cited_by_count":10,"area":"mllm"},{"id":"2502.20503","title":"Protecting multimodal large language models against misleading visualizations","created":"2025-02-27","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":"2602.04802","title":"VISTA-Bench: Do Vision-Language Models Really Understand Visualized Text as Well as Pure Text?","created":"2026-02-04","cited_by_count":8,"area":"mllm"},{"id":"2507.20174","title":"LRR-Bench: Left, Right or Rotate? Vision-Language models Still Struggle With Spatial Understanding Tasks","created":"2025-07-27","cited_by_count":6,"area":"mllm"},{"id":"2509.10105","title":"VARCO-VISION-2.0 Technical Report","created":"2025-09-12","cited_by_count":6,"area":"mllm"},{"id":"2509.14769","title":"Frame Sampling Strategies Matter: A Benchmark for small vision language models","created":"2025-09-18","cited_by_count":6,"area":"mllm"},{"id":"2512.22238","title":"Masking Teacher and Reinforcing Student for Distilling Vision-Language Models","created":"2025-12-23","cited_by_count":6,"area":"mllm"},{"id":"2503.23730","title":"KOFFVQA: An Objectively Evaluated Free-form VQA Benchmark for Large Vision-Language Models in the Korean Language","created":"2025-03-31","cited_by_count":5,"area":"mllm"},{"id":"2508.00399","title":"iSafetyBench: A video-language benchmark for safety in industrial environment","created":"2025-08-01","cited_by_count":5,"area":"mllm"},{"id":"2509.19018","title":"OmniBridge: Unified Multimodal Understanding, Generation, and Retrieval via Latent Space Alignment","created":"2025-09-23","cited_by_count":5,"area":"mllm"},{"id":"2510.14866","title":"Benchmarking Multimodal Large Language Models for Face Recognition","created":"2025-10-16","cited_by_count":5,"area":"mllm"},{"id":"2512.08374","title":"The Unseen Bias: How Norm Discrepancy in Pre-Norm MLLMs Leads to Visual Information Loss","created":"2025-12-09","cited_by_count":5,"area":"mllm"},{"id":"2606.13870","title":"Mirage Probes: How Vision Models Fake Visual Understanding","created":"2026-06-11","cited_by_count":5,"area":"mllm"},{"id":"2606.14703","title":"Gaze Heads: How VLMs Look at What They Describe","created":"2026-06-12","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":"2501.14276","title":"Global Semantic-Guided Sub-image Feature Weight Allocation in High-Resolution Large Vision-Language Models","created":"2025-01-24","cited_by_count":4,"area":"mllm"},{"id":"2507.01643","title":"SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement","created":"2025-07-02","cited_by_count":4,"area":"mllm"},{"id":"2507.03123","title":"Investigating VLM Hallucination from a Cognitive Psychology Perspective: A First Step Toward Interpretation with Intriguing Observations","created":"2025-07-03","cited_by_count":4,"area":"mllm"},{"id":"2509.09658","title":"Measuring Epistemic Humility in Multimodal Large Language Models","created":"2025-09-11","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":"2511.19032","title":"Diagnosing Corruption-Induced Reliability Failures in Vision-Language Models","created":"2025-11-24","cited_by_count":4,"area":"mllm"},{"id":"2503.06019","title":"GenieBlue: Integrating both Linguistic and Multimodal Capabilities for Large Language Models on Mobile Devices","created":"2025-03-08","cited_by_count":3,"area":"mllm"},{"id":"2508.15164","title":"ContextualLVLM-Agent: A Holistic Framework for Multi-Turn Visually-Grounded Dialogue and Complex Instruction Following","created":"2025-08-21","cited_by_count":3,"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":"2511.22787","title":"World in a Frame: Understanding Culture Mixing as a New Challenge for Vision-Language Models","created":"2025-11-27","cited_by_count":3,"area":"mllm"},{"id":"2411.14725","title":"Evaluating and Advancing Multimodal Large Language Models in Perception Ability Lens","created":"2024-11-22","cited_by_count":2,"area":"mllm"},{"id":"2503.09348","title":"MOAT: Evaluating LMMs for Capability Integration and Instruction Grounding","created":"2025-03-12","cited_by_count":2,"area":"mllm"},{"id":"2504.12018","title":"Instruction-augmented Multimodal Alignment for Image-Text and Element Matching","created":"2025-04-16","cited_by_count":2,"area":"mllm"},{"id":"2510.08352","title":"Evaluating Small Vision-Language Models on Distance-Dependent Traffic Perception","created":"2025-10-09","cited_by_count":2,"area":"mllm"},{"id":"2512.01419","title":"Rice-VL: Evaluating Vision-Language Models for Cultural Understanding Across ASEAN Countries","created":"2025-12-01","cited_by_count":2,"area":"mllm"},{"id":"2512.10554","title":"Grounding Everything in Tokens for Multimodal Large Language Models","created":"2025-12-11","cited_by_count":2,"area":"mllm"},{"id":"2606.25634","title":"SSMNBench: Diagnosing Image-based Cross-View Human-Object Understanding via Single-View Sufficiency and Multi-View Necessity","created":"2026-06-24","cited_by_count":2,"area":"mllm"},{"id":"2504.12316","title":"Data Metabolism: An Efficient Data Design Schema For Vision Language Model","created":"2025-04-10","cited_by_count":1,"area":"mllm"},{"id":"2506.19079","title":"Reading Smiles: Proxy Bias in Foundation Models for Facial Emotion Recognition","created":"2025-06-23","cited_by_count":1,"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":"2510.25682","title":"PairUni: Pairwise Training for Unified Multimodal Language Models","created":"2025-10-29","cited_by_count":1,"area":"mllm"},{"id":"2511.16600","title":"You Only Forward Once: An Efficient Compositional Judging Paradigm","created":"2025-11-20","cited_by_count":1,"area":"mllm"},{"id":"2601.19507","title":"Automated Safety Benchmarking: A Multi-agent Pipeline for LVLMs","created":"2026-01-27","cited_by_count":1,"area":"mllm"},{"id":"2603.25613","title":"Demographic Fairness in Multimodal LLMs: A Benchmark of Gender and Ethnicity Bias in Face Verification","created":"2026-03-26","cited_by_count":1,"area":"mllm"},{"id":"2506.20214","title":"UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation","created":"2025-06-25","cited_by_count":0,"area":"mllm"},{"id":"2507.15285","title":"In-context Learning of Vision Language Models for Detection of Physical and Digital Attacks against Face Recognition Systems","created":"2025-07-21","cited_by_count":0,"area":"mllm"},{"id":"2511.07171","title":"Federated Learning for Video Violence Detection: Complementary Roles of Lightweight CNNs and Vision-Language Models for Energy-Efficient Use","created":"2025-11-10","cited_by_count":0,"area":"mllm"},{"id":"2603.22321","title":"From Instructions to Assistance: a Dataset Aligning Instruction Manuals with Assembly Videos for Evaluating Multimodal LLMs","created":"2026-03-20","cited_by_count":0,"area":"mllm"},{"id":"2603.29759","title":"TSHA: A Benchmark for Visual Language Models in Trustworthy Safety Hazard Assessment Scenarios","created":"2026-03-31","cited_by_count":0,"area":"mllm"},{"id":"2605.10576","title":"SenseBench: A Benchmark for Remote Sensing Low-Level Visual Perception and Description in Large Vision-Language Models","created":"2026-05-11","cited_by_count":0,"area":"mllm"},{"id":"2605.17823","title":"Why We Look Where We Look: Emergent Human-like Fixations of a Foveated Visual Language Model Maximizing Scene Understanding","created":"2026-05-18","cited_by_count":0,"area":"mllm"},{"id":"2606.31187","title":"Learning to Deny: Action Denial in Multimodal Large Language Models","created":"2026-06-30","cited_by_count":0,"area":"mllm"},{"id":"2607.16305","title":"LookME: Lookup-Based Multimodal Embeddings for Layer Injection in Vision-Language Models","created":"2026-07-14","cited_by_count":0,"area":"mllm"},{"id":"2608.08630","title":"VLZip: Unified Visual and Textual Compression for Interleaved Long-Context Modeling","created":"2026-08-09","cited_by_count":0,"area":"mllm"},{"id":"2608.29802","title":"Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detection","created":"2026-08-30","cited_by_count":0,"area":"mllm"},{"id":"2610.11363","title":"UniData: Universal Multimodal Instruction Generation Pipeline","created":"2026-10-08","cited_by_count":0,"area":"mllm"},{"id":"2610.15467","title":"Semantic Saliency from Multi-Modal Large Language Model Scene Understanding Maps","created":"2026-10-11","cited_by_count":0,"area":"mllm"},{"id":"2610.19892","title":"On the Limits of Representation-Based Test-Time Adaptation for Multimodal LLMs","created":"2026-10-14","cited_by_count":0,"area":"mllm"}],"next_cursor":null}