{"total":64,"rows":[{"id":"2311.17005","title":"MVBench: A Comprehensive Multi-modal Video Understanding Benchmark","created":"2023-11-28","cited_by_count":1109,"area":"mllm"},{"id":"2406.16852","title":"Long Context Transfer from Language to Vision","created":"2024-06-24","cited_by_count":515,"area":"mllm"},{"id":"2410.17434","title":"LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding","created":"2024-10-22","cited_by_count":356,"area":"mllm"},{"id":"2404.16994","title":"PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning","created":"2024-04-25","cited_by_count":322,"area":"mllm"},{"id":"2406.10721","title":"RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics","created":"2024-06-15","cited_by_count":251,"area":"mllm"},{"id":"2408.16500","title":"CogVLM2: Visual Language Models for Image and Video Understanding","created":"2024-08-29","cited_by_count":217,"area":"mllm"},{"id":"2406.14515","title":"MMBench-Video: A Long-Form Multi-Shot Benchmark for Holistic Video Understanding","created":"2024-06-20","cited_by_count":182,"area":"mllm"},{"id":"2601.10611","title":"Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding","created":"2026-01-15","cited_by_count":139,"area":"mllm"},{"id":"2408.15542","title":"Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input","created":"2024-08-28","cited_by_count":134,"area":"mllm"},{"id":"2404.18532","title":"MileBench: Benchmarking MLLMs in Long Context","created":"2024-04-29","cited_by_count":88,"area":"mllm"},{"id":"2501.07888","title":"Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding","created":"2025-01-14","cited_by_count":81,"area":"mllm"},{"id":"2501.02955","title":"MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models","created":"2025-01-06","cited_by_count":70,"area":"mllm"},{"id":"2504.15271","title":"Eagle 2.5: Boosting Long-Context Post-Training for Frontier Vision-Language Models","created":"2025-04-21","cited_by_count":64,"area":"mllm"},{"id":"2501.08282","title":"LLaVA-ST: A Multimodal Large Language Model for Fine-Grained Spatial-Temporal Understanding","created":"2025-01-14","cited_by_count":59,"area":"mllm"},{"id":"2311.09048","title":"GRASP: A novel benchmark for evaluating language GRounding And Situated Physics understanding in multimodal language models","created":"2023-11-15","cited_by_count":28,"area":"mllm"},{"id":"2412.09616","title":"V2PE: Improving Multimodal Long-Context Capability of Vision-Language Models with Variable Visual Position Encoding","created":"2024-12-12","cited_by_count":28,"area":"mllm"},{"id":"2503.13983","title":"SpaceVLLM: Endowing Multimodal Large Language Model with Spatio-Temporal Video Grounding Capability","created":"2025-03-18","cited_by_count":28,"area":"mllm"},{"id":"2412.09613","title":"PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models","created":"2024-12-12","cited_by_count":25,"area":"mllm"},{"id":"2406.14129","title":"Towards Event-oriented Long Video Understanding","created":"2024-06-20","cited_by_count":21,"area":"mllm"},{"id":"2501.10604","title":"When language and vision meet road safety: leveraging multimodal large language models for video-based traffic accident analysis","created":"2025-01-17","cited_by_count":21,"area":"mllm"},{"id":"2401.15071","title":"From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities","created":"2024-01-26","cited_by_count":19,"area":"mllm"},{"id":"2406.00622","title":"Compositional 4D Dynamic Scenes Understanding with Physics Priors for Video Question Answering","created":"2024-06-02","cited_by_count":18,"area":"mllm"},{"id":"2512.22748","title":"TrimTokenator-LC: Towards Adaptive Visual Token Pruning for Large Multimodal Models with Long Contexts","created":"2025-12-28","cited_by_count":14,"area":"mllm"},{"id":"2311.14580","title":"Large Language Models as Automated Aligners for benchmarking Vision-Language Models","created":"2023-11-24","cited_by_count":10,"area":"mllm"},{"id":"2412.16158","title":"HoVLE: Unleashing the Power of Monolithic Vision-Language Models with Holistic Vision-Language Embedding","created":"2024-12-20","cited_by_count":10,"area":"mllm"},{"id":"2501.05067","title":"LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding","created":"2025-01-09","cited_by_count":10,"area":"mllm"},{"id":"2510.13251","title":"Map the Flow: Revealing Hidden Pathways of Information in VideoLLMs","created":"2025-10-15","cited_by_count":10,"area":"mllm"},{"id":"2409.14993","title":"Multi-modal Generative AI: Multi-modal LLMs, Diffusions, and the Unification","created":"2024-09-23","cited_by_count":8,"area":"mllm"},{"id":"2504.07454","title":"How Can Objects Help Video-Language Understanding?","created":"2025-04-10","cited_by_count":8,"area":"mllm"},{"id":"2506.08708","title":"PhyBlock: A Progressive Benchmark for Physical Understanding and Planning via 3D Block Assembly","created":"2025-06-10","cited_by_count":7,"area":"mllm"},{"id":"2603.06569","title":"Penguin-VL: Exploring the Efficiency Limits of VLM with LLM-based Vision Encoders","created":"2026-03-06","cited_by_count":7,"area":"mllm"},{"id":"2408.02231","title":"REVISION: Rendering Tools Enable Spatial Fidelity in Vision-Language Models","created":"2024-08-05","cited_by_count":6,"area":"mllm"},{"id":"2507.20174","title":"LRR-Bench: Left, Right or Rotate? Vision-Language models Still Struggle With Spatial Understanding Tasks","created":"2025-07-27","cited_by_count":6,"area":"mllm"},{"id":"2412.12833","title":"FocusChat: Text-guided Long Video Understanding via Spatiotemporal Information Filtering","created":"2024-12-17","cited_by_count":5,"area":"mllm"},{"id":"2506.07032","title":"A Culturally-diverse Multilingual Multimodal Video Benchmark & Model","created":"2025-06-08","cited_by_count":5,"area":"mllm"},{"id":"2511.20272","title":"VKnowU: Evaluating Visual Knowledge Understanding in Multimodal LLMs","created":"2025-11-25","cited_by_count":5,"area":"mllm"},{"id":"2604.14149","title":"One Token per Highly Selective Frame: Towards Extreme Compression for Long Video Understanding","created":"2026-04-15","cited_by_count":5,"area":"mllm"},{"id":"2608.13167","title":"TRAPSBench: Vision-Language Models Encode but Fail to Express Epistemic Restraint","created":"2026-08-13","cited_by_count":5,"area":"mllm"},{"id":"2402.12079","title":"LVCHAT: Facilitating Long Video Comprehension","created":"2024-02-19","cited_by_count":4,"area":"mllm"},{"id":"2503.09445","title":"Astrea: A MOE-based Visual Understanding Model with Progressive Alignment","created":"2025-03-12","cited_by_count":3,"area":"mllm"},{"id":"2505.18855","title":"Inference Compute-Optimal Video Vision Language Models","created":"2025-05-24","cited_by_count":3,"area":"mllm"},{"id":"2507.16572","title":"Pixels to Principles: Probing Intuitive Physics Understanding in Multimodal Language Models","created":"2025-07-22","cited_by_count":3,"area":"mllm"},{"id":"2602.17869","title":"Learning Compact Video Representations for Efficient Long-form Video Understanding in Large Multimodal Models","created":"2026-02-19","cited_by_count":3,"area":"mllm"},{"id":"2603.08436","title":"Can Vision-Language Models Solve the Shell Game?","created":"2026-03-09","cited_by_count":3,"area":"mllm"},{"id":"2509.12263","title":"InPhyRe Discovers: Large Multimodal Models Struggle in Inductive Physical Reasoning","created":"2025-09-12","cited_by_count":2,"area":"mllm"},{"id":"2512.11336","title":"UFVideo: Towards Unified Fine-Grained Video Cooperative Understanding with Large Language Models","created":"2025-12-12","cited_by_count":2,"area":"mllm"},{"id":"2507.22933","title":"Augmented Vision-Language Models: A Systematic Review","created":"2025-07-24","cited_by_count":1,"area":"mllm"},{"id":"2510.06251","title":"Physics Knowledge in Frontier Models: A Diagnostic Study of Failure Modes","created":"2025-10-03","cited_by_count":1,"area":"mllm"},{"id":"2512.06673","title":"Detector-Empowered Video Large Language Model for Efficient Spatio-Temporal Grounding","created":"2025-12-07","cited_by_count":1,"area":"mllm"},{"id":"2603.06828","title":"Step-Level Visual Grounding Faithfulness Predicts Out-of-Distribution Generalization in Long-Horizon Vision-Language Models","created":"2026-03-06","cited_by_count":1,"area":"mllm"},{"id":"2605.01662","title":"Video Active Perception: Effective Inference-Time Long-Form Video Understanding with Vision-Language Models","created":"2026-05-03","cited_by_count":1,"area":"mllm"},{"id":"2608.10949","title":"StreamFlow: Dynamic Memory Flows for Streaming Video Understanding","created":"2026-08-11","cited_by_count":1,"area":"mllm"},{"id":"2502.15079","title":"Can Hallucination Correction Improve Video-Language Alignment?","created":"2025-02-20","cited_by_count":0,"area":"mllm"},{"id":"2507.10302","title":"DisCo: Towards Distinct and Coherent Visual Encapsulation in Video MLLMs","created":"2025-07-14","cited_by_count":0,"area":"mllm"},{"id":"2603.14953","title":"Learning Question-Aware Keyframe Selection with Synthetic Supervision for Video Question Answering","created":"2026-03-16","cited_by_count":0,"area":"mllm"},{"id":"2603.16958","title":"PhysQuantAgent: An Inference Pipeline of Mass Estimation for Vision-Language Models","created":"2026-03-17","cited_by_count":0,"area":"mllm"},{"id":"2604.11136","title":"BoxTuning: Directly Injecting the Object Box for Multimodal Model Fine-Tuning","created":"2026-04-13","cited_by_count":0,"area":"mllm"},{"id":"2606.31187","title":"Learning to Deny: Action Denial in Multimodal Large Language Models","created":"2026-06-30","cited_by_count":0,"area":"mllm"},{"id":"2607.09029","title":"MOSAIC: Adaptive Inter-layer Composition for Efficient Heterogeneous Vision-Language Models","created":"2026-07-10","cited_by_count":0,"area":"mllm"},{"id":"2608.05505","title":"DynaPix: Can Vision-Language Models Identify the Exact Future?","created":"2026-08-06","cited_by_count":0,"area":"mllm"},{"id":"2608.06756","title":"Capek 0.5: An Execution-Centric Vision-Language Model for Embodied Intelligence","created":"2026-08-07","cited_by_count":0,"area":"mllm"},{"id":"2608.23474","title":"What's the Catch? Evaluating Temporal Consistency in Vision-Language Models","created":"2026-08-24","cited_by_count":0,"area":"mllm"},{"id":"2609.39588","title":"KilometerVision: A New Frontier for Large-Scale Spatial Intelligence in VLMs","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}