{"total":133,"rows":[{"id":"2501.13106","title":"VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding","created":"2025-01-22","cited_by_count":518,"area":null},{"id":"2501.05510","title":"OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?","created":"2025-01-09","cited_by_count":142,"area":null},{"id":"2504.17343","title":"TimeChat-Online: 80% Visual Tokens are Naturally Redundant in Streaming Videos","created":"2025-04-24","cited_by_count":97,"area":null},{"id":"2503.03803","title":"EgoLife: Towards Egocentric Life Assistant","created":"2025-03-05","cited_by_count":91,"area":null},{"id":"2501.00599","title":"VideoRefer Suite: Advancing Spatial-Temporal Object Understanding with Video LLM","created":"2024-12-31","cited_by_count":72,"area":null},{"id":"2505.05467","title":"StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant","created":"2025-05-08","cited_by_count":63,"area":null},{"id":"2503.11187","title":"FastVID: Dynamic Density Pruning for Fast Video Large Language Models","created":"2025-03-14","cited_by_count":52,"area":null},{"id":"2505.23189","title":"TrackVLA: Embodied Visual Tracking in the Wild","created":"2025-05-29","cited_by_count":47,"area":null},{"id":"2604.02317","title":"A Simple Baseline for Streaming Video Understanding","created":"2026-04-02","cited_by_count":33,"area":null},{"id":"2503.18943","title":"SlowFast-LLaVA-1.5: A Family of Token-Efficient Video Large Language Models for Long-Form Video Understanding","created":"2025-03-24","cited_by_count":30,"area":null},{"id":"2507.13353","title":"VideoITG: Multimodal Video Understanding with Instructed Temporal Grounding","created":"2025-07-17","cited_by_count":29,"area":null},{"id":"2603.02096","title":"FluxMem: Adaptive Hierarchical Memory for Streaming Video Understanding","created":"2026-03-02","cited_by_count":28,"area":null},{"id":"2512.21334","title":"Streaming Video Instruction Tuning","created":"2025-12-24","cited_by_count":26,"area":null},{"id":"2503.09590","title":"BIMBA: Selective-Scan Compression for Long-Range Video Question Answering","created":"2025-03-12","cited_by_count":24,"area":null},{"id":"2603.19217","title":"LVOmniBench: Pioneering Long Audio-Video Understanding Evaluation for Omnimodal LLMs","created":"2026-03-19","cited_by_count":24,"area":null},{"id":"2504.16082","title":"MR. Video: \"MapReduce\" is the Principle for Long Video Understanding","created":"2025-04-22","cited_by_count":23,"area":null},{"id":"2510.12422","title":"VideoLucy: Deep Memory Backtracking for Long Video Understanding","created":"2025-10-14","cited_by_count":22,"area":null},{"id":"2411.16771","title":"VidHal: Benchmarking Temporal Hallucinations in Vision LLMs","created":"2024-11-25","cited_by_count":19,"area":null},{"id":"2507.11336","title":"UGC-VideoCaptioner: An Omni UGC Video Detail Caption Model and New Benchmarks","created":"2025-07-15","cited_by_count":19,"area":null},{"id":"2603.08620","title":"StreamReady: Learning What to Answer and When in Long Streaming Videos","created":"2026-03-09","cited_by_count":19,"area":null},{"id":"2502.03183","title":"MaxInfo: A Training-Free Key-Frame Selection Method Using Maximum Volume for Enhanced Video Understanding","created":"2025-02-05","cited_by_count":18,"area":null},{"id":"2506.00993","title":"FlexSelect: Flexible Token Selection for Efficient Long Video Understanding","created":"2025-06-01","cited_by_count":18,"area":null},{"id":"2503.14378","title":"Impossible Videos","created":"2025-03-18","cited_by_count":16,"area":null},{"id":"2603.12938","title":"Thinking in Streaming Video","created":"2026-03-13","cited_by_count":16,"area":null},{"id":"2604.04184","title":"AURA: Always-On Understanding and Real-Time Assistance via Video Streams","created":"2026-04-05","cited_by_count":16,"area":null},{"id":"2501.06835","title":"X-LeBench: A Benchmark for Extremely Long Egocentric Video Understanding","created":"2025-01-12","cited_by_count":15,"area":null},{"id":"2503.21459","title":"RoadSocial: A Diverse VideoQA Dataset and Benchmark for Road Event Understanding from Social Video Narratives","created":"2025-03-27","cited_by_count":15,"area":null},{"id":"2501.05037","title":"LongViTU: Instruction Tuning for Long-Form Video Understanding","created":"2025-01-09","cited_by_count":13,"area":null},{"id":"2602.15329","title":"EventMemAgent: Hierarchical Event-Centric Memory for Online Video Understanding with Adaptive Tool Use","created":"2026-02-17","cited_by_count":12,"area":null},{"id":"2505.22810","title":"VidText: Towards Comprehensive Evaluation for Video Text Understanding","created":"2025-05-28","cited_by_count":11,"area":null},{"id":"2602.13191","title":"CoPE-VideoLM: Leveraging Codec Primitives For Efficient Video Language Modeling","created":"2026-02-13","cited_by_count":11,"area":null},{"id":"2504.01407","title":"ZoomV: Temporal Zoom-in for Efficient Long Video Understanding","created":"2025-04-02","cited_by_count":10,"area":null},{"id":"2504.16030","title":"LiveCC: Learning Video LLM with Streaming Speech Transcription at Scale","created":"2025-04-22","cited_by_count":9,"area":null},{"id":"2507.02591","title":"AuroraLong: Bringing RNNs Back to Efficient Open-Ended Video Understanding","created":"2025-07-03","cited_by_count":9,"area":null},{"id":"2510.02262","title":"From Frames to Clips: Training-free Adaptive Key Clip Selection for Long-Form Video Understanding","created":"2025-10-02","cited_by_count":9,"area":null},{"id":"2510.02778","title":"AdaRD-key: Adaptive Relevance-Diversity Keyframe Sampling for Long-form Video understanding","created":"2025-10-03","cited_by_count":9,"area":null},{"id":"2510.05836","title":"Flow4Agent: Long-form Video Understanding via Motion Prior from Optical Flow","created":"2025-10-07","cited_by_count":9,"area":null},{"id":"2512.14273","title":"Zoom-Zero: Reinforced Coarse-to-Fine Video Understanding via Temporal Zoom-in","created":"2025-12-16","cited_by_count":8,"area":null},{"id":"2603.25072","title":"GIFT: Global Irreplaceability Frame Targeting for Efficient Video Understanding","created":"2026-03-26","cited_by_count":8,"area":null},{"id":"2605.07897","title":"Semantic-Aware Adaptive Visual Memory for Streaming Video Understanding","created":"2026-05-08","cited_by_count":8,"area":null},{"id":"2503.20540","title":"Beyond Intermediate States: Explaining Visual Redundancy through Language","created":"2025-03-26","cited_by_count":7,"area":null},{"id":"2505.23617","title":"One Trajectory, One Token: Grounded Video Tokenization via Panoptic Sub-object Trajectory","created":"2025-05-29","cited_by_count":7,"area":null},{"id":"2512.03575","title":"UniComp: Rethinking Video Compression Through Informational Uniqueness","created":"2025-12-03","cited_by_count":7,"area":null},{"id":"2602.20913","title":"LongVideo-R1: Smart Navigation for Low-cost Long Video Understanding","created":"2026-02-24","cited_by_count":7,"area":null},{"id":"2603.19054","title":"Em-Garde: A Propose-Match Framework for Proactive Streaming Video Understanding","created":"2026-03-19","cited_by_count":7,"area":null},{"id":"2606.02569","title":"AdaCodec: A Predictive Visual Code for Video MLLMs","created":"2026-06-01","cited_by_count":7,"area":null},{"id":"2606.16353","title":"What Should a Streaming Video Model Remember?","created":"2026-06-15","cited_by_count":7,"area":null},{"id":"2512.14017","title":"KFS-Bench: Comprehensive Evaluation of Key Frame Sampling in Long Video Understanding","created":"2025-12-16","cited_by_count":6,"area":null},{"id":"2501.14194","title":"ENTER: Event Based Interpretable Reasoning for VideoQA","created":"2025-01-24","cited_by_count":5,"area":null},{"id":"2510.20622","title":"SeViCES: Unifying Semantic-Visual Evidence Consensus for Long Video Understanding","created":"2025-10-23","cited_by_count":5,"area":null},{"id":"2510.26113","title":"EgoExo-Con: Exploring View-Invariant Video Temporal Understanding","created":"2025-10-30","cited_by_count":5,"area":null},{"id":"2603.17840","title":"Video Understanding: From Geometry and Semantics to Unified Models","created":"2026-03-18","cited_by_count":5,"area":null},{"id":"2604.18459","title":"Progressive Online Video Understanding with Evidence-Aligned Timing and Transparent Decisions","created":"2026-04-20","cited_by_count":5,"area":null},{"id":"2605.10343","title":"EvoStreaming: Your Offline Video Model Is a Natively Streaming Assistant","created":"2026-05-11","cited_by_count":5,"area":null},{"id":"2607.11523","title":"Vinci2: Providing Proactive Assistance in Continuous Egocentric Videos","created":"2026-07-13","cited_by_count":5,"area":null},{"id":"2607.28312","title":"ObjectStream: Latent Objects as Memory Anchors for Streaming Video Understanding","created":"2026-07-30","cited_by_count":5,"area":null},{"id":"2505.19155","title":"Sparse-to-Dense: A Free Lunch for Lossless Acceleration of Video Understanding in LLMs","created":"2025-05-25","cited_by_count":4,"area":null},{"id":"2510.11129","title":"video-SALMONN S: Memory-Enhanced Streaming Audio-Visual LLM","created":"2025-10-13","cited_by_count":4,"area":null},{"id":"2512.00694","title":"Affordance-First Decomposition for Continual Learning in Video-Language Understanding","created":"2025-11-30","cited_by_count":4,"area":null},{"id":"2604.05079","title":"SVAgent: Storyline-Guided Long Video Understanding via Cross-Modal Multi-Agent Collaboration","created":"2026-04-06","cited_by_count":4,"area":null},{"id":"2605.17921","title":"An Efficient Streaming Video Understanding Framework with Agentic Control","created":"2026-05-18","cited_by_count":4,"area":null},{"id":"2606.07577","title":"OmniMem: Perturbation-aware Memory Compression for Streaming Audio-Visual LLMs","created":"2026-05-26","cited_by_count":4,"area":null},{"id":"2606.19341","title":"Native Active Perception as Reasoning for Omni-Modal Understanding","created":"2026-06-17","cited_by_count":4,"area":null},{"id":"2607.13298","title":"FOLIO: Focused Semantic Memory for Streaming Video Understanding","created":"2026-07-14","cited_by_count":4,"area":null},{"id":"2508.07401","title":"LET-US: Long Event-Text Understanding of Scenes","created":"2025-08-10","cited_by_count":3,"area":null},{"id":"2509.24563","title":"NeMo: Needle in a Montage for Video-Language Understanding","created":"2025-09-29","cited_by_count":3,"area":null},{"id":"2603.04349","title":"FocusGraph: Graph-Structured Frame Selection for Embodied Long Video Question Answering","created":"2026-03-04","cited_by_count":3,"area":null},{"id":"2605.12056","title":"OmniRefine: Alignment-Aware Cooperative Compression for Efficient Omnimodal Large Language Models","created":"2026-05-12","cited_by_count":3,"area":null},{"id":"2609.00291","title":"StreamScout: Learning When to Look Deeper for Streaming Video Understanding","created":"2026-08-31","cited_by_count":3,"area":null},{"id":"2505.23272","title":"Are MLMs Trapped in the Visual Room?","created":"2025-05-29","cited_by_count":2,"area":null},{"id":"2507.09068","title":"Infinite Video Understanding","created":"2025-07-11","cited_by_count":2,"area":null},{"id":"2508.13692","title":"HumanPCR: Probing MLLM Capabilities in Diverse Human-Centric Scenes","created":"2025-08-19","cited_by_count":2,"area":null},{"id":"2509.17901","title":"Do Modern Video-LLMs Need to Listen? A Benchmark Audit and Scalable Remedy","created":"2025-09-22","cited_by_count":2,"area":null},{"id":"2601.20742","title":"Compression Tells Intelligence: Visual Coding, Visual Token Technology, and the Unification","created":"2026-01-28","cited_by_count":2,"area":null},{"id":"2604.18573","title":"T-REN: Learning Text-Aligned Region Tokens Improves Dense Vision-Language Alignment and Scalability","created":"2026-04-20","cited_by_count":2,"area":null},{"id":"2604.19564","title":"EgoSelf: From Memory to Personalized Egocentric Assistant","created":"2026-04-21","cited_by_count":2,"area":null},{"id":"2605.04045","title":"Audio-Visual Intelligence in Large Foundation Models","created":"2026-05-05","cited_by_count":2,"area":null},{"id":"2605.07575","title":"Response-G1: Explicit Scene Graph Modeling for Proactive Streaming Video Understanding","created":"2026-05-08","cited_by_count":2,"area":null},{"id":"2605.17260","title":"LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMs","created":"2026-05-17","cited_by_count":2,"area":null},{"id":"2605.18018","title":"See What I Mean: Aligning Vision and Language Representations for Video Fine-grained Object Understanding","created":"2026-05-18","cited_by_count":2,"area":null},{"id":"2605.22678","title":"Swift Sampling: Selecting Temporal Surprises via Taylor Series","created":"2026-05-21","cited_by_count":2,"area":null},{"id":"2607.28516","title":"Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding","created":"2026-07-30","cited_by_count":2,"area":null},{"id":"2608.22516","title":"TRACE: Temporal Retrieval with Anchored and Convergent Evidence for Long-Horizon Video Understanding","created":"2026-08-23","cited_by_count":2,"area":null},{"id":"2504.10443","title":"Multimodal Long Video Modeling Based on Temporal Dynamic Context","created":"2025-04-14","cited_by_count":1,"area":null},{"id":"2504.21403","title":"Static or Dynamic: Towards Query-Adaptive Token Selection for Video Question Answering","created":"2025-04-30","cited_by_count":1,"area":null},{"id":"2505.19853","title":"Two Causally Related Needles in a Video Haystack","created":"2025-05-26","cited_by_count":1,"area":null},{"id":"2507.07135","title":"FACap: A Large-scale Fashion Dataset for Fine-grained Composed Image Retrieval","created":"2025-07-08","cited_by_count":1,"area":null},{"id":"2601.02908","title":"TA-Prompting: Enhancing Video Large Language Models for Dense Video Captioning via Temporal Anchors","created":"2026-01-06","cited_by_count":1,"area":null},{"id":"2601.07366","title":"HiVid-Narrator: Hierarchical Video Narrative Generation with Scene-Primed ASR-anchored Compression","created":"2026-01-12","cited_by_count":1,"area":null},{"id":"2603.22872","title":"ForeSea: AI Forensic Search with Multi-modal Queries for Video Surveillance","created":"2026-03-24","cited_by_count":1,"area":null},{"id":"2604.17873","title":"Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models","created":"2026-04-20","cited_by_count":1,"area":null},{"id":"2605.06809","title":"LookWhen? Fast Video Recognition by Learning When, Where, and What to Compute","created":"2026-05-07","cited_by_count":1,"area":null},{"id":"2605.09223","title":"CREST: Curvature-Regulated Event-Centric Sampling for Efficient Long-Video Understanding","created":"2026-05-09","cited_by_count":1,"area":null},{"id":"2605.19075","title":"CRAFT: Critic-Refined Adaptive Key-Frame Targeting for Multimodal Video Question Answering","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2605.21988","title":"Learning Spatiotemporal Sensitivity in Video LLMs via Counterfactual Reinforcement Learning","created":"2026-05-21","cited_by_count":1,"area":null},{"id":"2606.20711","title":"Video2Code: Generating Interactive Webpages from UI Videos via Action-Aware Revisit","created":"2026-06-16","cited_by_count":1,"area":null},{"id":"2606.24602","title":"ViTexQA: A Multi-Frame Temporal Perception Dataset for Video Text Question Answering","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2606.26762","title":"ProtoKV: Streaming Video Understanding under Delayed Query with Summary-State Memory","created":"2026-06-25","cited_by_count":1,"area":null},{"id":"2606.30026","title":"MuseBench: Benchmarking Intent-Level Audiovisual Arts Understanding in MLLMs","created":"2026-06-29","cited_by_count":1,"area":null},{"id":"2608.03918","title":"When and Where to Look: Adaptive Visual Evidence Scheduling for Efficient Long Video Understanding","created":"2026-08-04","cited_by_count":1,"area":null}],"next_cursor":"100"}