{"total":35,"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":"2507.07999","title":"Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Methodology","created":"2025-07-10","cited_by_count":69,"area":null},{"id":"2412.04383","title":"SeeGround: See and Ground for Zero-Shot Open-Vocabulary 3D Visual Grounding","created":"2024-12-05","cited_by_count":67,"area":null},{"id":"2604.24954","title":"Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence","created":"2026-04-27","cited_by_count":30,"area":null},{"id":"2505.23504","title":"VAU-R1: Advancing Video Anomaly Understanding via Reinforcement Fine-Tuning","created":"2025-05-29","cited_by_count":24,"area":null},{"id":"2504.07089","title":"OmniCaptioner: One Captioner to Rule Them All","created":"2025-04-09","cited_by_count":20,"area":null},{"id":"2502.18778","title":"M2-omni: Advancing Omni-MLLM for Comprehensive Modality Support with Competitive Performance","created":"2025-02-26","cited_by_count":19,"area":null},{"id":"2505.08137","title":"Large Language Models for Computer-Aided Design: A Survey","created":"2025-05-13","cited_by_count":18,"area":null},{"id":"2507.20804","title":"MMGraphRAG: Bridging Vision and Language with Interpretable Multimodal Knowledge Graphs","created":"2025-07-28","cited_by_count":16,"area":null},{"id":"2505.16836","title":"Fact-R1: Towards Explainable Video Misinformation Detection with Deep Reasoning","created":"2025-05-22","cited_by_count":14,"area":null},{"id":"2504.09255","title":"FVQ: A Large-Scale Dataset and an LMM-based Method for Face Video Quality Assessment","created":"2025-04-12","cited_by_count":13,"area":null},{"id":"2509.19274","title":"DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian Culture","created":"2025-09-23","cited_by_count":13,"area":null},{"id":"2510.08508","title":"MoA-VR: A Mixture-of-Agents System Towards All-in-One Video Restoration","created":"2025-10-09","cited_by_count":12,"area":null},{"id":"2601.20430","title":"Youtu-Parsing: Perception, Structuring and Recognition via High-Parallelism Decoding","created":"2026-01-28","cited_by_count":10,"area":null},{"id":"2503.13794","title":"LED: LLM Enhanced Open-Vocabulary Object Detection without Human Curated Data Generation","created":"2025-03-18","cited_by_count":8,"area":null},{"id":"2510.10231","title":"Semantic Visual Anomaly Detection and Reasoning in AI-Generated Images","created":"2025-10-11","cited_by_count":8,"area":null},{"id":"2504.15066","title":"Chinese-LiPS: A Chinese audio-visual speech recognition dataset with Lip-reading and Presentation Slides","created":"2025-04-21","cited_by_count":5,"area":null},{"id":"2505.19707","title":"MLLM-Guided VLM Fine-Tuning with Joint Inference for Zero-Shot Composed Image Retrieval","created":"2025-05-26","cited_by_count":5,"area":null},{"id":"2601.02752","title":"EComStage: Stage-wise and Orientation-specific Benchmarking for Large Language Models in E-commerce","created":"2026-01-06","cited_by_count":4,"area":null},{"id":"2502.04379","title":"Can Large Language Models Capture Video Game Engagement?","created":"2025-02-05","cited_by_count":3,"area":null},{"id":"2503.06885","title":"ProBench: Judging Multimodal Foundation Models on Open-ended Multi-domain Expert Tasks","created":"2025-03-10","cited_by_count":2,"area":null},{"id":"2511.08369","title":"Text-based Aerial-Ground Person Retrieval","created":"2025-11-11","cited_by_count":2,"area":null},{"id":"2511.21982","title":"DialBench: Towards Accurate Reading Recognition of Pointer Meter using Large Foundation Models","created":"2025-11-26","cited_by_count":2,"area":null},{"id":"2607.27826","title":"Sign Language Question Answering: A New Task, Benchmark, and Baseline for Sign Language Understanding","created":"2026-07-30","cited_by_count":2,"area":null},{"id":"2505.14660","title":"EmoGist: Efficient In-Context Learning for Visual Emotion Understanding","created":"2025-05-20","cited_by_count":1,"area":null},{"id":"2505.17235","title":"CHAOS: Chart Analysis with Outlier Samples","created":"2025-05-22","cited_by_count":1,"area":null},{"id":"2603.27223","title":"EuraGovExam: A Multilingual Multimodal Benchmark from Real-World Civil Service Exams","created":"2026-03-28","cited_by_count":1,"area":null},{"id":"2604.01306","title":"M2-Verify: A Large-Scale Multidomain Benchmark for Checking Multimodal Claim Consistency","created":"2026-04-01","cited_by_count":1,"area":null},{"id":"2505.15628","title":"SNAP: A Benchmark for Testing the Effects of Capture Conditions on Fundamental Vision Tasks","created":"2025-05-21","cited_by_count":0,"area":null},{"id":"2505.18168","title":"Emotion Knowledge Enhancement for Vision Large Language Models: A Self-Verification Approach for High-Quality Emotion Instruction Data Generation","created":"2025-05-14","cited_by_count":0,"area":null},{"id":"2508.08781","title":"SHREC 2025: Retrieval of Optimal Objects for Multi-modal Enhanced Language and Spatial Assistance (ROOMELSA)","created":"2025-08-12","cited_by_count":0,"area":null},{"id":"2604.07956","title":"MONETA: Multimodal Industry Classification through Geographic Information with Multi Agent Systems","created":"2026-04-09","cited_by_count":0,"area":null},{"id":"2608.07932","title":"SportsGrounder: Proposal-Aided Interleaved Grounding for Dense Sports Video Reasoning","created":"2026-08-08","cited_by_count":0,"area":null},{"id":"2608.08596","title":"Goal-oriented Navigation Instruction Generation with Tour Video Priors","created":"2026-08-09","cited_by_count":0,"area":null},{"id":"2609.26205","title":"LLaVA-Assessor: Building the Foundation LMM For Visual Quality Assessment","created":"2026-08-11","cited_by_count":0,"area":null}],"next_cursor":null}