{"total":122,"rows":[{"id":"2311.17982","title":"VBench: Comprehensive Benchmark Suite for Video Generative Models","created":"2023-11-29","cited_by_count":1822,"area":null},{"id":"2312.02051","title":"TimeChat: A Time-sensitive Multimodal Large Language Model for Long Video Understanding","created":"2023-12-04","cited_by_count":406,"area":"mllm"},{"id":"2503.21755","title":"VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness","created":"2025-03-27","cited_by_count":315,"area":"wm"},{"id":"2406.15252","title":"VideoScore: Building Automatic Metrics to Simulate Fine-grained Human Feedback for Video Generation","created":"2024-06-21","cited_by_count":197,"area":null},{"id":"2407.14505","title":"T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation","created":"2024-07-19","cited_by_count":185,"area":null},{"id":"2411.17440","title":"Identity-Preserving Text-to-Video Generation by Frequency Decomposition","created":"2024-11-26","cited_by_count":158,"area":null},{"id":"2504.00983","title":"WorldScore: A Unified Evaluation Benchmark for World Generation","created":"2025-04-01","cited_by_count":156,"area":null},{"id":"2403.06098","title":"VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models","created":"2024-03-10","cited_by_count":131,"area":"diffusion"},{"id":"2405.03520","title":"Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond","created":"2024-05-06","cited_by_count":111,"area":"wm"},{"id":"2412.14167","title":"VideoDPO: Omni-Preference Alignment for Video Diffusion Generation","created":"2024-12-18","cited_by_count":108,"area":"diffusion"},{"id":"2406.18522","title":"ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation","created":"2024-06-26","cited_by_count":75,"area":null},{"id":"2505.20292","title":"OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation","created":"2025-05-26","cited_by_count":73,"area":null},{"id":"2410.15458","title":"Allegro: Open the Black Box of Commercial-Level Video Generation Model","created":"2024-10-20","cited_by_count":70,"area":null},{"id":"2407.01094","title":"Evaluation of Text-to-Video Generation Models: A Dynamics Perspective","created":"2024-07-01","cited_by_count":67,"area":null},{"id":"2407.05965","title":"T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models","created":"2024-07-08","cited_by_count":66,"area":null},{"id":"2504.04907","title":"Video-Bench: Human-Aligned Video Generation Benchmark","created":"2025-04-07","cited_by_count":57,"area":"alignment"},{"id":"2311.17404","title":"VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models","created":"2023-11-29","cited_by_count":55,"area":null},{"id":"2403.05131","title":"Sora as a World Model? A Complete Survey on Text-to-Video Generation","created":"2024-03-08","cited_by_count":53,"area":"wm"},{"id":"2401.07781","title":"Towards A Better Metric for Text-to-Video Generation","created":"2024-01-15","cited_by_count":51,"area":null},{"id":"2503.10076","title":"VMBench: A Benchmark for Perception-Aligned Video Motion Generation","created":"2025-03-13","cited_by_count":49,"area":null},{"id":"2411.13503","title":"VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models","created":"2024-11-20","cited_by_count":45,"area":null},{"id":"2406.08656","title":"TC-Bench: Benchmarking Temporal Compositionality in Text-to-Video and Image-to-Video Generation","created":"2024-06-12","cited_by_count":43,"area":null},{"id":"2510.26802","title":"Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark","created":"2025-10-30","cited_by_count":43,"area":"lr"},{"id":"2403.11956","title":"Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessment","created":"2024-03-18","cited_by_count":39,"area":null},{"id":"2505.00337","title":"T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation","created":"2025-05-01","cited_by_count":39,"area":null},{"id":"2512.01989","title":"PAI-Bench: A Comprehensive Benchmark For Physical AI","created":"2025-12-01","cited_by_count":34,"area":"mllm"},{"id":"2601.15282","title":"Rethinking Video Generation Model for the Embodied World","created":"2026-01-21","cited_by_count":33,"area":null},{"id":"2406.06087","title":"GAIA: Rethinking Action Quality Assessment for AI-Generated Videos","created":"2024-06-10","cited_by_count":30,"area":null},{"id":"2412.16211","title":"Is Your World Simulator a Good Story Presenter? A Consecutive Events-Based Benchmark for Future Long Video Generation","created":"2024-12-17","cited_by_count":30,"area":null},{"id":"2401.01651","title":"AIGCBench: Comprehensive Evaluation of Image-to-Video Content Generated by AI","created":"2024-01-03","cited_by_count":27,"area":null},{"id":"2402.02085","title":"Detecting AI-Generated Video via Frame Consistency","created":"2024-02-03","cited_by_count":26,"area":null},{"id":"2409.00031","title":"Quality Assessment in the Era of Large Models: A Survey","created":"2024-08-17","cited_by_count":26,"area":null},{"id":"2411.17221","title":"AIGV-Assessor: Benchmarking and Evaluating the Perceptual Quality of Text-to-Video Generation with LMM","created":"2024-11-26","cited_by_count":24,"area":"mllm"},{"id":"2503.23452","title":"VideoGen-Eval: Agent-based System for Video Generation Evaluation","created":"2025-03-30","cited_by_count":23,"area":"agents"},{"id":"2410.16152","title":"Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models","created":"2024-10-21","cited_by_count":21,"area":"diffusion"},{"id":"2404.16687","title":"NTIRE 2024 Quality Assessment of AI-Generated Content Challenge","created":"2024-04-25","cited_by_count":20,"area":null},{"id":"2507.18107","title":"T2VWorldBench: A Benchmark for Evaluating World Knowledge in Text-to-Video Generation","created":"2025-07-24","cited_by_count":19,"area":null},{"id":"2511.13853","title":"Can World Simulators Reason? Gen-ViRe: A Generative Visual Reasoning Benchmark","created":"2025-11-17","cited_by_count":19,"area":"lr"},{"id":"2606.00793","title":"MBench: A Comprehensive Benchmark on Memory Capability for Video World Models","created":"2026-05-30","cited_by_count":18,"area":"wm"},{"id":"2408.14468","title":"K-Sort Arena: Efficient and Reliable Benchmarking for Generative Models via K-wise Human Preferences","created":"2024-08-26","cited_by_count":16,"area":null},{"id":"2412.04508","title":"Video Quality Assessment: A Comprehensive Survey","created":"2024-12-04","cited_by_count":15,"area":null},{"id":"2501.07647","title":"BlobGEN-Vid: Compositional Text-to-Video Generation with Blob Video Representations","created":"2025-01-13","cited_by_count":15,"area":"diffusion"},{"id":"2407.21408","title":"Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model","created":"2024-07-31","cited_by_count":13,"area":null},{"id":"2505.18078","title":"DanceTogether! Identity-Preserving Multi-Person Interactive Video Generation","created":"2025-05-23","cited_by_count":13,"area":null},{"id":"2512.02622","title":"RULER-Bench: Probing Rule-based Reasoning Abilities of Next-level Video Generation Models for Vision Foundation Intelligence","created":"2025-12-02","cited_by_count":13,"area":"lr"},{"id":"2412.09997","title":"GT23D-Bench: A Comprehensive General Text-to-3D Generation Benchmark","created":"2024-12-13","cited_by_count":12,"area":null},{"id":"2603.12310","title":"VQQA: An Agentic Approach for Video Evaluation and Quality Improvement","created":"2026-03-12","cited_by_count":12,"area":"agents"},{"id":"2606.20545","title":"Current World Models Lack a Persistent State Core","created":"2026-06-18","cited_by_count":12,"area":"wm"},{"id":"2606.27537","title":"MemoBench: Benchmarking World Modeling in Dynamically Changing Environments","created":"2026-06-25","cited_by_count":12,"area":"wm"},{"id":"2509.24427","title":"UI2V-Bench: An Understanding-based Image-to-video Generation Benchmark","created":"2025-09-29","cited_by_count":11,"area":"diffusion"},{"id":"2410.04171","title":"IV-Mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis","created":"2024-10-05","cited_by_count":10,"area":"diffusion"},{"id":"2412.11183","title":"OccScene: Semantic Occupancy-based Cross-task Mutual Learning for 3D Scene Generation","created":"2024-12-15","cited_by_count":10,"area":"diffusion"},{"id":"2504.04051","title":"Can You Count to Nine? A Human Evaluation Benchmark for Counting Limits in Modern Text-to-Video Models","created":"2025-04-05","cited_by_count":10,"area":"diffusion"},{"id":"2504.17180","title":"We'll Fix it in Post: Improving Text-to-Video Generation with Neuro-Symbolic Feedback","created":"2025-04-24","cited_by_count":10,"area":null},{"id":"2505.00209","title":"Direct Motion Models for Assessing Generated Videos","created":"2025-04-30","cited_by_count":10,"area":null},{"id":"2505.04946","title":"T2VTextBench: A Human Evaluation Benchmark for Textual Control in Video Generation Models","created":"2025-05-08","cited_by_count":10,"area":null},{"id":"2505.12098","title":"LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation","created":"2025-05-17","cited_by_count":10,"area":"mllm"},{"id":"2405.04133","title":"Exposing AI-generated Videos: A Benchmark Dataset and a Local-and-Global Temporal Defect Based Detection Method","created":"2024-05-07","cited_by_count":9,"area":null},{"id":"2411.16619","title":"Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric","created":"2024-11-25","cited_by_count":9,"area":null},{"id":"2411.16718","title":"Neuro-Symbolic Evaluation of Text-to-Video Models using Formal Verification","created":"2024-11-22","cited_by_count":9,"area":null},{"id":"2503.16867","title":"ETVA: Evaluation of Text-to-Video Alignment via Fine-grained Question Generation and Answering","created":"2025-03-21","cited_by_count":9,"area":"alignment"},{"id":"2506.14827","title":"DAVID-XR1: Detecting AI-Generated Videos with Explainable Reasoning","created":"2025-06-13","cited_by_count":9,"area":"lr"},{"id":"2510.14847","title":"ImagerySearch: Adaptive Test-Time Search for Video Generation Beyond Semantic Dependency Constraints","created":"2025-10-16","cited_by_count":9,"area":null},{"id":"2605.26244","title":"LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV","created":"2026-05-25","cited_by_count":9,"area":null},{"id":"2606.01164","title":"Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends","created":"2026-05-31","cited_by_count":8,"area":"wm"},{"id":"2412.18688","title":"Video Is Worth a Thousand Images: Exploring the Latest Trends in Long Video Generation","created":"2024-12-24","cited_by_count":7,"area":null},{"id":"2503.02341","title":"GRADEO: Towards Human-Like Evaluation for Text-to-Video Generation via Multi-Step Reasoning","created":"2025-03-04","cited_by_count":7,"area":null},{"id":"2504.20466","title":"LMME3DHF: Benchmarking and Evaluating Multimodal 3D Human Face Generation with LMMs","created":"2025-04-29","cited_by_count":7,"area":null},{"id":"2606.11670","title":"ARGUS: Stacked Multi-View Identity Mosaic Injection for Subject-Preserving Video Generation","created":"2026-06-10","cited_by_count":7,"area":null},{"id":"2501.08545","title":"T2VEval: Benchmark Dataset and Objective Evaluation Method for T2V-generated Videos","created":"2025-01-15","cited_by_count":6,"area":null},{"id":"2503.09949","title":"UVE: Are MLLMs Unified Evaluators for AI-Generated Videos?","created":"2025-03-13","cited_by_count":6,"area":null},{"id":"2506.02875","title":"NTIRE 2025 XGC Quality Assessment Challenge: Methods and Results","created":"2025-06-03","cited_by_count":6,"area":null},{"id":"2506.14404","title":"Causally Steered Diffusion for Automated Video Counterfactual Generation","created":"2025-06-17","cited_by_count":6,"area":"diffusion"},{"id":"2605.10434","title":"WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors","created":"2026-05-11","cited_by_count":6,"area":"alignment"},{"id":"2605.15199","title":"EntityBench: Towards Entity-Consistent Long-Range Multi-Shot Video Generation","created":"2026-05-14","cited_by_count":6,"area":null},{"id":"2605.26525","title":"ReCA: Multi-Shot Long Video Extrapolation via Recursive Context Allocation","created":"2026-05-26","cited_by_count":6,"area":null},{"id":"2606.09639","title":"CineDance: Towards Next-Generation Multi-Shot Long-Form Cinematic Audio-Video Generation","created":"2026-06-08","cited_by_count":6,"area":null},{"id":"2602.18057","title":"Temporal Consistency-Aware Text-to-Motion Generation","created":"2026-02-20","cited_by_count":5,"area":null},{"id":"2608.26336","title":"StreamAV-Bench: A Comprehensive Benchmark for Streaming Audio-Video Generation","created":"2026-08-26","cited_by_count":5,"area":null},{"id":"2406.08845","title":"Rethinking Human Evaluation Protocol for Text-to-Video Models: Enhancing Reliability,Reproducibility, and Practicality","created":"2024-06-13","cited_by_count":4,"area":null},{"id":"2501.18314","title":"AGAV-Rater: Adapting Large Multimodal Model for AI-Generated Audio-Visual Quality Assessment","created":"2025-01-30","cited_by_count":4,"area":"mllm"},{"id":"2505.23693","title":"VF-Eval: Evaluating Multimodal LLMs for Generating Feedback on AIGC Videos","created":"2025-05-29","cited_by_count":4,"area":"mllm"},{"id":"2510.07310","title":"MATRIX: Mask Track Alignment for Interaction-aware Video Generation","created":"2025-10-08","cited_by_count":4,"area":null},{"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":"2608.02603","title":"WorldExam: Benchmarking World Models from Apparent Appearance to Inherent Reactivity","created":"2026-08-03","cited_by_count":4,"area":"wm"},{"id":"2608.16859","title":"HarnessEval-W: Agentifying the Evaluation of Visual Worlds","created":"2026-08-17","cited_by_count":4,"area":"wm"},{"id":"2407.16552","title":"MicroEmo: Time-Sensitive Multimodal Emotion Recognition with Micro-Expression Dynamics in Video Dialogues","created":"2024-07-23","cited_by_count":3,"area":"mllm"},{"id":"2410.08534","title":"Quality Prediction of AI Generated Images and Videos: Emerging Trends and Opportunities","created":"2024-10-11","cited_by_count":3,"area":null},{"id":"2510.07546","title":"PickStyle: Video-to-Video Style Transfer with Context-Style Adapters","created":"2025-10-08","cited_by_count":3,"area":"diffusion"},{"id":"2604.10127","title":"VGA-Bench: A Unified Benchmark and Multi-Model Framework for Video Aesthetics and Generation Quality Evaluation","created":"2026-04-11","cited_by_count":3,"area":null},{"id":"2605.14269","title":"PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation","created":"2026-05-14","cited_by_count":3,"area":null},{"id":"2606.01481","title":"SafeGen-Bench: Benchmarking Safety in Image-Conditioned Text-to-Video Generation","created":"2026-05-31","cited_by_count":3,"area":"diffusion"},{"id":"2501.02706","title":"Multilevel Semantic-Aware Model for AI-Generated Video Quality Assessment","created":"2025-01-06","cited_by_count":2,"area":"diffusion"},{"id":"2502.16915","title":"Multi-Dimensional Quality Assessment for Text-to-3D Assets: Dataset and Model","created":"2025-02-24","cited_by_count":2,"area":"diffusion"},{"id":"2506.04715","title":"Towards Holistic Visual Quality Assessment of AI-Generated Videos: A LLM-Based Multi-Dimensional Evaluation Model","created":"2025-06-05","cited_by_count":2,"area":null},{"id":"2507.00808","title":"Multi-interaction TTS toward professional recording reproduction","created":"2025-07-01","cited_by_count":2,"area":null},{"id":"2509.08818","title":"GeneVA: A Dataset of Human Annotations for Generative Text to Video Artifacts","created":"2025-09-10","cited_by_count":2,"area":null},{"id":"2509.11589","title":"MVQA-68K: A Multi-dimensional and Causally-annotated Dataset with Quality Interpretability for Video Assessment","created":"2025-09-15","cited_by_count":2,"area":null},{"id":"2603.03485","title":"Phys4D: Fine-Grained Physics-Consistent 4D Modeling from Video Diffusion","created":"2026-03-03","cited_by_count":2,"area":"wm"},{"id":"2603.29186","title":"SLVMEval: Synthetic Meta Evaluation Benchmark for Text-to-Long Video Generation","created":"2026-03-31","cited_by_count":2,"area":null}],"next_cursor":"100"}