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cs.CV2026

STORM: Internalized Modeling for Spatial-Temporal Reasoning in Video-Language Models

Yiming Liang, Yixiao Chen, Yiyang Zhou +8

Many video reasoning tasks require tracking motion, temporal order, and evolving visual states across frames. Existing methods built on large vision-language models (LVLMs) often a…

cs.CV2026

PhyMotion: Structured 3D Motion Reward for Physics-Grounded Human Video Generation

Yidong Huang, Zun Wang, Han Lin +6

Generating realistic human motion is a central yet unsolved challenge in video generation. While reinforcement learning (RL)-based post-training has driven recent gains in general…

cs.CV2026

EgoMemReason: A Memory-Driven Reasoning Benchmark for Long-Horizon Egocentric Video Understanding

Ziyang Wang, Yue Zhang, Shoubin Yu +6

Next-generation visual assistants, such as smart glasses, embodied agents, and always-on life-logging systems, must reason over an entire day or more of continuous visual experienc…

cs.CV2026

Ego2Web: A Web Agent Benchmark Grounded in Egocentric Videos

Shoubin Yu, Lei Shu, Antoine Yang +6

Multimodal AI agents are increasingly automating complex real-world workflows that involve online web execution. However, current web-agent benchmarks suffer from a critical limita…

cs.CV2026

VisionCoach: Reinforcing Grounded Video Reasoning via Visual-Perception Prompting

Daeun Lee, Shoubin Yu, Yue Zhang +1

Video reasoning requires models to locate and track question-relevant evidence across frames. While reinforcement learning (RL) with verifiable rewards improves accuracy, it still…

cs.CV2025

StreamGaze: Gaze-Guided Temporal Reasoning and Proactive Understanding in Streaming Videos

Daeun Lee, Subhojyoti Mukherjee, Branislav Kveton +6

Streaming video understanding requires models not only to process temporally incoming frames, but also to anticipate user intention for realistic applications such as Augmented Rea…