{"total":479,"rows":[{"id":"2601.10611","title":"Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding","created":"2026-01-15","cited_by_count":139,"area":"mllm"},{"id":"2509.22186","title":"MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing","created":"2025-09-26","cited_by_count":116,"area":"mllm"},{"id":"2510.14528","title":"PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model","created":"2025-10-16","cited_by_count":89,"area":"mllm"},{"id":"2604.27393","title":"MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction","created":"2026-04-30","cited_by_count":78,"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":"2510.17771","title":"Seeing but Not Believing: Probing the Disconnect Between Visual Attention and Answer Correctness in VLMs","created":"2025-10-20","cited_by_count":55,"area":"mllm"},{"id":"2510.18269","title":"StreamingTOM: Streaming Token Compression for Efficient Video Understanding","created":"2025-10-21","cited_by_count":43,"area":"mllm"},{"id":"2601.03309","title":"VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models","created":"2026-01-06","cited_by_count":39,"area":"mllm"},{"id":"2605.25979","title":"LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence","created":"2026-05-25","cited_by_count":39,"area":"mllm"},{"id":"2511.11007","title":"VisMem: Latent Vision Memory Unlocks Potential of Vision-Language Models","created":"2025-11-14","cited_by_count":37,"area":"mllm"},{"id":"2510.25616","title":"Don't Blind Your VLA: Aligning Visual Representations for OOD Generalization","created":"2025-10-29","cited_by_count":35,"area":"mllm"},{"id":"2512.01989","title":"PAI-Bench: A Comprehensive Benchmark For Physical AI","created":"2025-12-01","cited_by_count":34,"area":"mllm"},{"id":"2605.12500","title":"SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture","created":"2026-05-12","cited_by_count":32,"area":"mllm"},{"id":"2510.27350","title":"RzenEmbed: Towards Comprehensive Multimodal Retrieval","created":"2025-10-31","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":"2510.10991","title":"A Survey on Agentic Multimodal Large Language Models","created":"2025-10-13","cited_by_count":23,"area":"mllm"},{"id":"2601.07779","title":"OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agent","created":"2026-01-12","cited_by_count":21,"area":"mllm"},{"id":"2511.19575","title":"HunyuanOCR Technical Report","created":"2025-11-24","cited_by_count":20,"area":"mllm"},{"id":"2512.04540","title":"VideoMem: Enhancing Ultra-Long Video Understanding via Adaptive Memory Management","created":"2025-12-04","cited_by_count":19,"area":"mllm"},{"id":"2510.14979","title":"From Pixels to Words -- Towards Native Vision-Language Primitives at Scale","created":"2025-10-16","cited_by_count":18,"area":"mllm"},{"id":"2510.18876","title":"Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMs","created":"2025-10-21","cited_by_count":18,"area":"mllm"},{"id":"2602.15397","title":"ActionCodec: What Makes for Good Action Tokenizers","created":"2026-02-17","cited_by_count":18,"area":"mllm"},{"id":"2509.22496","title":"Where MLLMs Attend and What They Rely On: Explaining Autoregressive Token Generation","created":"2025-09-26","cited_by_count":16,"area":"mllm"},{"id":"2509.16197","title":"MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer","created":"2025-09-19","cited_by_count":15,"area":"mllm"},{"id":"2510.17777","title":"SparseVILA: Decoupling Visual Sparsity for Efficient VLM Inference","created":"2025-10-20","cited_by_count":15,"area":"mllm"},{"id":"2511.21662","title":"Multi-Crit: Benchmarking Multimodal Judges on Pluralistic Criteria-Following","created":"2025-11-26","cited_by_count":15,"area":"mllm"},{"id":"2603.28069","title":"MolmoPoint: Better Pointing for VLMs with Grounding Tokens","created":"2026-03-30","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":"2510.20707","title":"Mixing Importance with Diversity: Joint Optimization for KV Cache Compression in Large Vision-Language Models","created":"2025-10-23","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":"2512.14068","title":"SDAR-VL: Stable and Efficient Block-wise Diffusion for Vision-Language Understanding","created":"2025-12-16","cited_by_count":13,"area":"mllm"},{"id":"2601.17814","title":"MMR-Bench: A Comprehensive Benchmark for Multimodal LLM Routing","created":"2026-01-25","cited_by_count":13,"area":"mllm"},{"id":"2601.21639","title":"OCRVerse: Towards Holistic OCR in End-to-End Vision-Language Models","created":"2026-01-29","cited_by_count":12,"area":"mllm"},{"id":"2602.03060","title":"IVC-Prune: Revealing the Implicit Visual Coordinates in LVLMs for Vision Token Pruning","created":"2026-02-03","cited_by_count":12,"area":"mllm"},{"id":"2510.13891","title":"K-frames: Scene-Driven Any-k Keyframe Selection for long video understanding","created":"2025-10-14","cited_by_count":11,"area":"mllm"},{"id":"2510.16598","title":"VisionSelector: End-to-End Learnable Visual Token Compression for Efficient Multimodal LLMs","created":"2025-10-18","cited_by_count":11,"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":"2511.15690","title":"MoDES: Accelerating Mixture-of-Experts Multimodal Large Language Models via Dynamic Expert Skipping","created":"2025-11-19","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":"2512.15649","title":"VTCBench: Can Vision-Language Models Understand Long Context with Vision-Text Compression?","created":"2025-12-17","cited_by_count":11,"area":"mllm"},{"id":"2601.22575","title":"PhoStream: Benchmarking Real-World Streaming for Omnimodal Assistants in Mobile Scenarios","created":"2026-01-30","cited_by_count":10,"area":"mllm"},{"id":"2602.07026","title":"Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models","created":"2026-02-02","cited_by_count":10,"area":"mllm"},{"id":"2602.07574","title":"ViCA: Efficient Multimodal LLMs with Vision-Only Cross-Attention","created":"2026-02-07","cited_by_count":10,"area":"mllm"},{"id":"2511.18434","title":"DocPTBench: Benchmarking End-to-End Photographed Document Parsing and Translation","created":"2025-11-23","cited_by_count":9,"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":"2603.12254","title":"Attend Before Attention: Efficient and Scalable Video Understanding via Autoregressive Gazing","created":"2026-03-12","cited_by_count":9,"area":"mllm"},{"id":"2609.00111","title":"Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving","created":"2026-08-31","cited_by_count":9,"area":"mllm"},{"id":"2602.01816","title":"Seeing Is Believing? A Benchmark for Multimodal Large Language Models on Visual Illusions and Anomalies","created":"2026-02-02","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":"2602.08439","title":"Demo-ICL: In-Context Learning for Procedural Video Knowledge Acquisition","created":"2026-02-09","cited_by_count":8,"area":"mllm"},{"id":"2605.28820","title":"From Pixels to Words -- Towards Native One-Vision Models at Scale","created":"2026-05-27","cited_by_count":8,"area":"mllm"},{"id":"2606.10400","title":"Do Vision-Language Models See or Guess? Measuring and Reducing Textual-Prior Reliance with a Phrasing-Controlled Benchmark","created":"2026-06-09","cited_by_count":8,"area":"mllm"},{"id":"2510.17722","title":"MT-Video-Bench: A Holistic Video Understanding Benchmark for Evaluating Multimodal LLMs in Multi-Turn Dialogues","created":"2025-10-20","cited_by_count":7,"area":"mllm"},{"id":"2512.05745","title":"ARGUS: Defending Against Multimodal Indirect Prompt Injection via Steering Instruction-Following Behavior","created":"2025-12-05","cited_by_count":7,"area":"mllm"},{"id":"2601.03590","title":"Can LLMs See Without Pixels? Benchmarking Spatial Intelligence from Textual Descriptions","created":"2026-01-07","cited_by_count":7,"area":"mllm"},{"id":"2603.06569","title":"Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders","created":"2026-03-06","cited_by_count":7,"area":"mllm"},{"id":"2603.18472","title":"Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding","created":"2026-03-19","cited_by_count":7,"area":"mllm"},{"id":"2603.23885","title":"Towards Real-World Document Parsing via Realistic Scene Synthesis and Document-Aware Training","created":"2026-03-25","cited_by_count":7,"area":"mllm"},{"id":"2604.01569","title":"VideoZeroBench: Probing the Limits of Video MLLMs with Spatio-Temporal Evidence Verification","created":"2026-04-02","cited_by_count":7,"area":"mllm"},{"id":"2604.01966","title":"Ego-Grounding for Personalized Question-Answering in Egocentric Videos","created":"2026-04-02","cited_by_count":7,"area":"mllm"},{"id":"2509.26165","title":"Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models","created":"2025-09-30","cited_by_count":6,"area":"mllm"},{"id":"2510.12793","title":"ViCO: A Training Strategy towards Semantic Aware Dynamic High-Resolution","created":"2025-10-14","cited_by_count":6,"area":"mllm"},{"id":"2511.19524","title":"VideoChat-M1: Collaborative Policy Planning for Video Understanding via Multi-Agent Reinforcement Learning","created":"2025-11-24","cited_by_count":6,"area":"mllm"},{"id":"2511.21750","title":"SO-Bench: A Structural Output Evaluation of Multimodal LLMs","created":"2025-11-23","cited_by_count":6,"area":"mllm"},{"id":"2512.09663","title":"IF-Bench: Benchmarking and Enhancing MLLMs for Infrared Images with Generative Visual Prompting","created":"2025-12-10","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":"2604.11102","title":"OmniScript: Towards Audio-Visual Script Generation for Long-Form Cinematic Video","created":"2026-04-13","cited_by_count":6,"area":"mllm"},{"id":"2605.28548","title":"GEM: Generative Supervision Helps Embodied Intelligence","created":"2026-05-27","cited_by_count":6,"area":"mllm"},{"id":"2606.03890","title":"OVO-S-Bench: A Hierarchical Benchmark for Streaming Spatial Intelligence in Multimodal LLMs","created":"2026-06-02","cited_by_count":6,"area":"mllm"},{"id":"2607.24447","title":"RP-OPSD: Resolution-Privileged On-Policy Self-Distillation for Multimodal Large Language Models","created":"2026-07-27","cited_by_count":6,"area":"mllm"},{"id":"2509.22415","title":"Evidence Recomposition and Predictive Context Residualization for Visual Attribution in Multimodal Large Language Models","created":"2025-09-26","cited_by_count":5,"area":"mllm"},{"id":"2511.07738","title":"From Exploration to Exploitation: A Two-Stage Entropy RLVR Approach for Noise-Tolerant MLLM Training","created":"2025-11-11","cited_by_count":5,"area":"mllm"},{"id":"2511.20272","title":"VKnowU: Evaluating Visual Knowledge Understanding in Multimodal LLMs","created":"2025-11-25","cited_by_count":5,"area":"mllm"},{"id":"2512.23592","title":"Same or Not? Enhancing Visual Perception in Vision-Language Models","created":"2025-12-29","cited_by_count":5,"area":"mllm"},{"id":"2602.07038","title":"UNIKIE-BENCH: Benchmarking Large Multimodal Models for Key Information Extraction in Visual Documents","created":"2026-02-03","cited_by_count":5,"area":"mllm"},{"id":"2602.13662","title":"LeafNet: A Large-Scale Dataset and Comprehensive Benchmark for Foundational Vision-Language Understanding of Plant Diseases","created":"2026-02-14","cited_by_count":5,"area":"mllm"},{"id":"2602.21054","title":"VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation","created":"2026-02-24","cited_by_count":5,"area":"mllm"},{"id":"2603.00490","title":"LifeEval: A Multimodal Benchmark for Assistive AI in Egocentric Daily Life Tasks","created":"2026-02-28","cited_by_count":5,"area":"mllm"},{"id":"2603.11219","title":"Senna-2: Aligning VLM and End-to-End Driving Policy for Consistent Decision Making and Planning","created":"2026-03-11","cited_by_count":5,"area":"mllm"},{"id":"2603.13779","title":"AD-Copilot: A Vision-Language Assistant for Industrial Anomaly Detection via Visual In-context Comparison","created":"2026-03-14","cited_by_count":5,"area":"mllm"},{"id":"2604.08120","title":"Small Vision-Language Models are Smart Compressors for Long Video Understanding","created":"2026-04-09","cited_by_count":5,"area":"mllm"},{"id":"2605.10893","title":"Grounded or Guessing? LVLM Confidence Estimation via Blind-Image Contrastive Ranking","created":"2026-05-11","cited_by_count":5,"area":"mllm"},{"id":"2606.02522","title":"Moment-Video: Diagnosing Temporal Fidelity of Video MLLMs on Momentary Visual Events","created":"2026-06-01","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":"2606.24187","title":"Towards Fast and Effective Long Video Understanding of Multimodal Large Language Models via Adaptive Quasi-Gaussian Sampling","created":"2026-06-23","cited_by_count":5,"area":"mllm"},{"id":"2607.03358","title":"Pathways of Visual Information Flow in Vision-Language Models","created":"2026-07-03","cited_by_count":5,"area":"mllm"},{"id":"2510.02987","title":"TIT-Score: Evaluating Long-Prompt Based Text-to-Image Alignment via Text-to-Image-to-Text Consistency","created":"2025-10-03","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":"2510.18262","title":"UWBench: A Comprehensive Vision-Language Benchmark for Underwater Understanding","created":"2025-10-21","cited_by_count":4,"area":"mllm"},{"id":"2511.17699","title":"Understanding Counting Mechanisms in Large Language and Vision-Language Models","created":"2025-11-21","cited_by_count":4,"area":"mllm"},{"id":"2512.01248","title":"TRivia: Self-supervised Fine-tuning of Vision-Language Models for Table Recognition","created":"2025-12-01","cited_by_count":4,"area":"mllm"},{"id":"2601.04734","title":"AIVD: Adaptive Edge-Cloud Collaboration for Accurate and Efficient Industrial Visual Detection","created":"2026-01-08","cited_by_count":4,"area":"mllm"},{"id":"2602.06013","title":"GenArena: How Can We Achieve Human-Aligned Evaluation for Visual Generation Tasks?","created":"2026-02-05","cited_by_count":4,"area":"mllm"},{"id":"2602.11824","title":"Revis: Sparse Latent Steering to Mitigate Object Hallucination in Large Vision-Language Models","created":"2026-02-12","cited_by_count":4,"area":"mllm"},{"id":"2603.09326","title":"OddGridBench: Exposing the Lack of Fine-Grained Visual Discrepancy Sensitivity in Multimodal Large Language Models","created":"2026-03-10","cited_by_count":4,"area":"mllm"},{"id":"2603.09826","title":"VLM-Loc: Localization in Point Cloud Maps via Vision-Language Models","created":"2026-03-10","cited_by_count":4,"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":"2603.17662","title":"FINER: MLLMs Hallucinate under Fine-grained Negative Queries","created":"2026-03-18","cited_by_count":4,"area":"mllm"},{"id":"2603.18558","title":"HiMu: Hierarchical Multimodal Frame Selection for Long Video Question Answering","created":"2026-03-19","cited_by_count":4,"area":"mllm"},{"id":"2603.22187","title":"Seeing is Improving: Visual Feedback for Iterative Text Layout Refinement","created":"2026-03-23","cited_by_count":4,"area":"mllm"}],"next_cursor":"100"}