Video-MME
Emerging30papers using it
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Papers using Video-MME (30)
- Task-Focused Memorization for Multimodal AgentsNative Active Perception as Reasoning for Omni-Modal UnderstandingXiaomi Mimo-vl-miloco Technical ReportMorphoQuant: Modality-Aware Quantization for Omni-modal Large Language ModelsReflect-R1: Evidence-Driven Reflection for Self-Correction in Long Video UnderstandingVisReflect: Latent Visual Reflection for Fine-Grained Perception in Long Visual ContextDynin-Omni: Omnimodal Unified Large Diffusion Language ModelWhere to Focus: Query-Modulated Multimodal Keyframe Selection for Long Video UnderstandingEvent-Anchored Frame Selection for Effective Long-Video UnderstandingEvoPrune: Early-Stage Visual Token Pruning for Efficient MLLMsBeyond Single-Sample: Reliable Multi-Sample Distillation for Video UnderstandingQuestion-guided Visual Compression with Memory Feedback for Long-Term Video UnderstandingHiMu: Hierarchical Multimodal Frame Selection for Long Video Question AnsweringLensWalk: Agentic Video Understanding by Planning How You See in VideosMACD: Model-Aware Contrastive Decoding via Counterfactual DataMSJoE: Jointly Evolving MLLM and Sampler for Efficient Long-Form Video UnderstandingLinMU: Multimodal Understanding Made LinearScaling Vision Language Models for Pharmaceutical Long Form Video Reasoning on Industrial GenAI PlatformVideo Evidence to Reasoning Efficient Video Understanding via Explicit Evidence GroundingThink-Clip-Sample: Slow-Fast Frame Selection for Video UnderstandingLiViBench: An Omnimodal Benchmark for Interactive Livestream Video UnderstandingStructured Over Scale: Learning Spatial Reasoning from Educational VideoVideoAnchor: Reinforcing Subspace-Structured Visual Cues for Coherent Visual-Spatial ReasoningScaling RL To Long VideosVSI: Visual Subtitle Integration For Keyframe Selection To Enhance Long Video UnderstandingLightweight Structured Multimodal Reasoning For Clinical Scene Understanding In RoboticsEnhancing Temporal Understanding In Video-llms Through Stacked Temporal Attention In Vision EncodersLess Is More: Token-efficient Video-qa Via Adaptive Frame-pruning And Semantic Graph IntegrationQ-Frame: Query-aware Frame Selection and Multi-Resolution Adaptation for Video-LLMsVideo-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis