{"total":67,"rows":[{"id":"2504.10479","title":"InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models","created":"2025-04-14","cited_by_count":1834,"area":null},{"id":"2412.05271","title":"Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling","created":"2024-12-06","cited_by_count":1599,"area":"lr"},{"id":"2508.18265","title":"InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency","created":"2025-08-25","cited_by_count":1510,"area":"lr"},{"id":"2505.23764","title":"MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence","created":"2025-05-29","cited_by_count":183,"area":"lr"},{"id":"2501.16411","title":"PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding","created":"2025-01-27","cited_by_count":160,"area":"mllm"},{"id":"2410.13085","title":"MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models","created":"2024-10-16","cited_by_count":85,"area":"mllm"},{"id":"2408.15769","title":"A Survey on Evaluation of Multimodal Large Language Models","created":"2024-08-28","cited_by_count":46,"area":"lr"},{"id":"2412.09530","title":"Dynamic-VLM: Simple Dynamic Visual Token Compression for VideoLLM","created":"2024-12-12","cited_by_count":32,"area":"mllm"},{"id":"2412.19326","title":"Task Preference Optimization: Improving Multimodal Large Language Models with Vision Task Alignment","created":"2024-12-26","cited_by_count":29,"area":"mllm"},{"id":"2505.05456","title":"SITE: towards Spatial Intelligence Thorough Evaluation","created":"2025-05-08","cited_by_count":29,"area":null},{"id":"2409.18142","title":"A Survey on Multimodal Benchmarks: In the Era of Large AI Models","created":"2024-09-21","cited_by_count":27,"area":"mllm"},{"id":"2505.17012","title":"SpatialScore: Towards Comprehensive Evaluation for Spatial Intelligence","created":"2025-05-22","cited_by_count":24,"area":"mllm"},{"id":"2501.05767","title":"Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models","created":"2025-01-10","cited_by_count":22,"area":"mllm"},{"id":"2410.21259","title":"AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?","created":"2024-10-28","cited_by_count":21,"area":"mllm"},{"id":"2506.04280","title":"Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark","created":"2025-06-04","cited_by_count":21,"area":"lr"},{"id":"2505.03735","title":"Multi-Agent System for Comprehensive Soccer Understanding","created":"2025-05-06","cited_by_count":18,"area":"agents"},{"id":"2505.21076","title":"DynamicVL: Benchmarking Multimodal Large Language Models for Dynamic City Understanding","created":"2025-05-27","cited_by_count":18,"area":"mllm"},{"id":"2501.04670","title":"Are They the Same? Exploring Visual Correspondence Shortcomings of Multimodal LLMs","created":"2025-01-08","cited_by_count":16,"area":"lr"},{"id":"2603.28069","title":"MolmoPoint: Better Pointing for VLMs with Grounding Tokens","created":"2026-03-30","cited_by_count":15,"area":"mllm"},{"id":"2509.01907","title":"RSCC: A Large-Scale Remote Sensing Change Caption Dataset for Disaster Events","created":"2025-09-02","cited_by_count":14,"area":null},{"id":"2503.15024","title":"Forensics-Bench: A Comprehensive Forgery Detection Benchmark Suite for Large Vision Language Models","created":"2025-03-19","cited_by_count":13,"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":"2508.15802","title":"MAC: A Live Benchmark for Multimodal Large Language Models in Scientific Understanding","created":"2025-08-14","cited_by_count":12,"area":"mllm"},{"id":"2506.14907","title":"PeRL: Permutation-Enhanced Reinforcement Learning for Interleaved Vision-Language Reasoning","created":"2025-06-17","cited_by_count":11,"area":"lr"},{"id":"2507.00748","title":"Improving the Reasoning of Multi-Image Grounding in MLLMs via Reinforcement Learning","created":"2025-07-01","cited_by_count":11,"area":"lr"},{"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":"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":"2506.06727","title":"VisioMath: Benchmarking Figure-based Mathematical Reasoning in LMMs","created":"2025-06-07","cited_by_count":6,"area":"lr"},{"id":"2501.13620","title":"A Cognitive Paradigm Approach to Probe the Perception-Reasoning Interface in VLMs","created":"2025-01-23","cited_by_count":5,"area":"lr"},{"id":"2512.23365","title":"SpatialMosaic: A Multiview VLM Dataset for Partial Visibility","created":"2025-12-29","cited_by_count":5,"area":"lr"},{"id":"2604.20806","title":"OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Model","created":"2026-04-22","cited_by_count":5,"area":"lr"},{"id":"2509.19245","title":"ConViS-Bench: Estimating Video Similarity Through Semantic Concepts","created":"2025-09-23","cited_by_count":4,"area":null},{"id":"2604.26934","title":"World2VLM: Distilling World Model Imagination into VLMs for Dynamic Spatial Reasoning","created":"2026-04-29","cited_by_count":4,"area":"wm"},{"id":"2501.03675","title":"SMIR: Efficient Synthetic Data Pipeline To Improve Multi-Image Reasoning","created":"2025-01-07","cited_by_count":3,"area":"lr"},{"id":"2511.16786","title":"Revisiting Multimodal KV Cache Compression: A Frequency-Domain-Guided Outlier-KV-Aware Approach","created":"2025-11-20","cited_by_count":3,"area":"mllm"},{"id":"2512.06759","title":"VisChainBench: A Benchmark for Multi-Turn, Multi-Image Visual Reasoning Beyond Language Priors","created":"2025-12-07","cited_by_count":3,"area":"lr"},{"id":"2603.05697","title":"MultiHaystack: Benchmarking Multimodal Retrieval and Reasoning over 40K Images, Videos, and Documents","created":"2026-03-05","cited_by_count":3,"area":"lr"},{"id":"2606.14383","title":"IndustryBench-MIPU: Benchmarking Multi-Image Attribute Value Extraction for Industrial Products","created":"2026-06-12","cited_by_count":3,"area":null},{"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":"2505.23065","title":"SNS-Bench-VL: Benchmarking Multimodal Large Language Models in Social Networking Services","created":"2025-05-29","cited_by_count":2,"area":"mllm"},{"id":"2506.18140","title":"See-in-Pairs: Reference Image-Guided Comparative Vision-Language Models for Medical Diagnosis","created":"2025-06-22","cited_by_count":2,"area":"mllm"},{"id":"2508.13692","title":"HumanPCR: Probing MLLM Capabilities in Diverse Human-Centric Scenes","created":"2025-08-19","cited_by_count":2,"area":null},{"id":"2602.03454","title":"Contextualized Visual Personalization in Vision-Language Models","created":"2026-02-03","cited_by_count":2,"area":"mllm"},{"id":"2603.19466","title":"ProactiveBench: Benchmarking Proactiveness in Multimodal Large Language Models","created":"2026-03-19","cited_by_count":2,"area":"mllm"},{"id":"2604.01634","title":"CRIT: Graph-Based Automatic Data Synthesis to Enhance Cross-Modal Multi-Hop Reasoning","created":"2026-04-02","cited_by_count":2,"area":"lr"},{"id":"2505.11141","title":"Human-Aligned Bench: Fine-Grained Assessment of Reasoning Ability in MLLMs vs. Humans","created":"2025-05-16","cited_by_count":1,"area":"lr"},{"id":"2506.11080","title":"MANBench: Is Your Multimodal Model Smarter than Human?","created":"2025-06-04","cited_by_count":1,"area":"mllm"},{"id":"2511.03206","title":"QG-CoC: Question-Guided Chain-of-Captions for Large Multimodal Models","created":"2025-11-05","cited_by_count":1,"area":"mllm"},{"id":"2511.21251","title":"AVFakeBench: A Comprehensive Audio-Video Forgery Detection Benchmark for AV-LMMs","created":"2025-11-26","cited_by_count":1,"area":null},{"id":"2603.18004","title":"Unified Spatio-Temporal Token Scoring for Efficient Video VLMs","created":"2026-03-18","cited_by_count":1,"area":"mllm"},{"id":"2605.11591","title":"Logit-Attention Divergence: Mitigating Position Bias in Multi-Image Retrieval via Attention-Guided Calibration","created":"2026-05-12","cited_by_count":1,"area":"mllm"},{"id":"2503.19361","title":"ImageSet2Text: Describing Sets of Images through Text","created":"2025-03-25","cited_by_count":0,"area":null},{"id":"2507.07574","title":"Beyond the Linear Separability Ceiling: Aligning Representations in VLMs","created":"2025-07-10","cited_by_count":0,"area":"mllm"},{"id":"2511.03768","title":"What's in Common? Multimodal Models Hallucinate When Reasoning Across Scenes","created":"2025-11-05","cited_by_count":0,"area":"lr"},{"id":"2603.04676","title":"Decoding the Pulse of Reasoning VLMs in Multi-Image Understanding Tasks","created":"2026-03-04","cited_by_count":0,"area":"lr"},{"id":"2603.28662","title":"AMIGO: Agentic Multi-Image Grounding Oracle Benchmark","created":"2026-03-30","cited_by_count":0,"area":"mllm"},{"id":"2604.27389","title":"COHERENCE: Benchmarking Fine-Grained Image-Text Alignment in Interleaved Multimodal Contexts","created":"2026-04-30","cited_by_count":0,"area":"mllm"},{"id":"2605.09883","title":"The Cartesian Shortcut: Re-evaluate Vision Reasoning in Polar Coordinate Space","created":"2026-05-11","cited_by_count":0,"area":"lr"},{"id":"2606.00148","title":"StemBind: When MLLMs Get Lost Between Rules and Instances in Abstract Visual Reasoning","created":"2026-05-29","cited_by_count":0,"area":"lr"},{"id":"2607.00576","title":"Safe Alone, Unsafe Together: Safeguarding Against Implicit Toxicity When Benign Images Combine","created":"2026-07-01","cited_by_count":0,"area":null},{"id":"2608.30653","title":"Fine-Grained Multi Image Object Hallucination Benchmark","created":"2026-08-31","cited_by_count":0,"area":"mllm"},{"id":"2609.39363","title":"Rethinking Multi-Image Re-Representation in Multi-Image Understanding","created":"2026-09-30","cited_by_count":0,"area":"lr"},{"id":"2610.12961","title":"MVGraph: Benchmarking LVLMs on Evidence Composition across Multi-View Visual Graph","created":"2026-10-09","cited_by_count":0,"area":"lr"},{"id":"2610.15129","title":"GesBench: When and Where Do Multimodal Language Models Perceive Social Meaning?","created":"2026-10-10","cited_by_count":0,"area":"mllm"},{"id":"2610.15915","title":"VIEWCRAFT: Evolving What Multimodal Agents See and How They Read It","created":"2026-10-11","cited_by_count":0,"area":null},{"id":"2610.18836","title":"Plan-Bench: Can Existing VLMs Go Well Beyond Perception to Reason and Plan in Embodied Worlds?","created":"2026-10-13","cited_by_count":0,"area":"lr"},{"id":"2610.18858","title":"Visual Tokens on Demand: Visual Budgeting for Scalable and Efficient Multi-Image Reasoning in Multimodal LLMs","created":"2026-10-13","cited_by_count":0,"area":"lr"}],"next_cursor":null}