{"total":40,"rows":[{"id":"2504.13074","title":"SkyReels-V2: Infinite-length Film Generative Model","created":"2025-04-17","cited_by_count":229,"area":"mllm"},{"id":"2501.00574","title":"VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling","created":"2024-12-31","cited_by_count":220,"area":"mllm"},{"id":"2501.12386","title":"InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling","created":"2025-01-21","cited_by_count":211,"area":"mllm"},{"id":"2406.07230","title":"Needle In A Multimodal Haystack","created":"2024-06-11","cited_by_count":58,"area":"mllm"},{"id":"2412.02617","title":"Improving Dynamic Object Interactions in Text-to-Video Generation with AI Feedback","created":"2024-12-03","cited_by_count":47,"area":"mllm"},{"id":"2501.02189","title":"A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges","created":"2025-01-04","cited_by_count":47,"area":"mllm"},{"id":"2408.09787","title":"Anim-Director: A Large Multimodal Model Powered Agent for Controllable Animation Video Generation","created":"2024-08-19","cited_by_count":37,"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":"2505.01481","title":"VideoHallu: Evaluating and Mitigating Multi-modal Hallucinations on Synthetic Video Understanding","created":"2025-05-02","cited_by_count":32,"area":"mllm"},{"id":"2504.14666","title":"Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens","created":"2025-04-20","cited_by_count":28,"area":"mllm"},{"id":"2502.14914","title":"CAPability: A Comprehensive Visual Caption Benchmark for Evaluating Both Correctness and Thoroughness","created":"2025-02-19","cited_by_count":25,"area":"mllm"},{"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":"2503.14935","title":"FAVOR-Bench: A Comprehensive Benchmark for Fine-Grained Video Motion Understanding","created":"2025-03-19","cited_by_count":24,"area":"mllm"},{"id":"2412.21080","title":"Vinci: A Real-time Embodied Smart Assistant based on Egocentric Vision-Language Model","created":"2024-12-30","cited_by_count":19,"area":"mllm"},{"id":"2509.22646","title":"Learning Human-Perceived Fakeness in AI-Generated Videos via Multimodal LLMs","created":"2025-09-26","cited_by_count":17,"area":"mllm"},{"id":"2407.08583","title":"The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective","created":"2024-07-11","cited_by_count":15,"area":"mllm"},{"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":"2508.05580","title":"Follow-Your-Instruction: A Comprehensive MLLM Agent for World Data Synthesis","created":"2025-08-07","cited_by_count":10,"area":"mllm"},{"id":"2509.23828","title":"Uni4D-LLM: A Unified SpatioTemporal-Aware VLM for 4D Understanding and Generation","created":"2025-09-28","cited_by_count":10,"area":"mllm"},{"id":"2507.00006","title":"MVGBench: Comprehensive Benchmark for Multi-view Generation Models","created":"2025-06-11","cited_by_count":9,"area":"mllm"},{"id":"2503.04250","title":"An Egocentric Vision-Language Model based Portable Real-time Smart Assistant","created":"2025-03-06","cited_by_count":8,"area":"mllm"},{"id":"2503.12545","title":"PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models","created":"2025-03-16","cited_by_count":6,"area":"mllm"},{"id":"2505.19901","title":"Dynamic-I2V: Exploring Image-to-Video Generation Models via Multimodal LLM","created":"2025-05-26","cited_by_count":6,"area":"mllm"},{"id":"2507.04909","title":"HumanVideo-MME: Benchmarking MLLMs for Human-Centric Video Understanding","created":"2025-07-07","cited_by_count":6,"area":"mllm"},{"id":"2508.10771","title":"AEGIS: Authenticity Evaluation Benchmark for AI-Generated Video Sequences","created":"2025-08-14","cited_by_count":6,"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":"2504.21435","title":"SeriesBench: A Benchmark for Narrative-Driven Drama Series Understanding","created":"2025-04-30","cited_by_count":5,"area":"mllm"},{"id":"2605.11723","title":"CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating","created":"2026-05-12","cited_by_count":5,"area":"mllm"},{"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":"2510.02987","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":"2512.11464","title":"Exploring MLLM-Diffusion Information Transfer with MetaCanvas","created":"2025-12-12","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":"2411.10867","title":"ViBe: A Text-to-Video Benchmark for Evaluating Hallucination in Large Multimodal Models","created":"2024-11-16","cited_by_count":3,"area":"mllm"},{"id":"2601.06600","title":"Probing Multimodal Large Language Models on Cognitive Biases in Chinese Short-Video Misinformation","created":"2026-01-10","cited_by_count":2,"area":"mllm"},{"id":"2602.05202","title":"GT-SVJ: Generative-Transformer-Based Self-Supervised Video Judge For Efficient Video Reward Modeling","created":"2026-02-05","cited_by_count":2,"area":"mllm"},{"id":"2508.11170","title":"Better Supervised Fine-tuning for VQA: Integer-Only Loss","created":"2025-08-15","cited_by_count":0,"area":"mllm"},{"id":"2605.20795","title":"What Semantics Survive the Connector? Diagnosing VLM-to-DiT Alignment in Video Editing","created":"2026-05-20","cited_by_count":0,"area":"mllm"},{"id":"2610.00666","title":"VisionQ: VLM-as-a-Judge Taxonomy, Dataset and Benchmark for Qualitative Analysis in Computer Vision","created":"2026-09-30","cited_by_count":0,"area":"mllm"},{"id":"2610.15722","title":"PhySimCode: A Benchmark and Evaluation Method for Physics Video to Code Generation","created":"2026-10-11","cited_by_count":0,"area":"mllm"}],"next_cursor":null}