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Guang-Yu Liu

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#artificial intelligence Preprint Nov 2026

WanderBench: Can World Models Explore Dynamic Worlds from Video?

Video world models conditioned on an input video make it possible to explore real, recorded dynamic scenes, enabling re-shooting of footage, free-viewpoint replay, and real-to-sim environments for embodied agents. Such uses require the generated rollout to stay faithful to the recorded world, yet existing benchmarks st...

Yu-Hang Chen, Jichuiyang Li, Jia-Le Wang et al. · 0 citations
#artificial intelligence Preprint Oct 2026

DIVE: Benchmarking Full-Duplex Interaction with Visual Engagement in Continuous Streams

This work introduces DIVE, a benchmark for evaluating full-duplex interaction with visual engagement under continuous and realistic multimodal streams and evaluates representative real-time models using response quality, window response rates, and reaction latency.

Yu-Hang Chen, Guang-Yu Liu, Shi-Long Liu · 0 citations

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