3 papers
cs.AI2026
SCOUT: Self-Checking and Recovery-Aware Tool-Thought Agents for Ultra-Long Egocentric Video Reasoning
Keyang Zhong, Kuo Wang, Peng Liu +5
Ultra-long egocentric video understanding requires reasoning over temporally sparse evidence distributed across hours or days, challenging current multimodal models with limited co…
cs.CV2025
Free-MoRef: Instantly Multiplexing Context Perception Capabilities of Video-MLLMs within Single Inference
Kuo Wang, Quanlong Zheng, Junlin Xie +6
Video Multimodal Large Language Models~(Video-MLLM) have achieved remarkable advancements in video understanding tasks. However, constrained by the context length limitation in the…
cs.CV2025
H2VU-Benchmark: A Comprehensive Benchmark for Hierarchical Holistic Video Understanding
Qi Wu, Quanlong Zheng, Yanhao Zhang +8
With the rapid development of multimodal models, the demand for assessing video understanding capabilities has been steadily increasing. However, existing benchmarks for evaluating…