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Shi Guo

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#artificial intelligence Review Oct 2026

Physical AI: Concepts, Techniques, and Challenges

This monograph seeks to define physical AI, present its technical landscape, and examine each key technical subfield in depth, and establishes a unified framework for Physical AI: artificial systems that perceive, model, and act upon the physical world through continuous feedback under real-world constraints.

Wei-Nan Zhang, Chun-Hua Shen, Tian-Fan Xue et al. · 0 citations
#artificial intelligence Preprint Oct 2026

FlashVSR+: Efficient Video Super-Resolution via Hybrid Attention and Reward-Yield Distribution Matching

Recent video super-resolution (VSR) models achieve efficient one-step generation through diffusion distillation. However, high-resolution inference remains costly, and distilled models are difficult to align with human preferences. These challenges call for improvements in both model architecture and training strategy....

Ru-Chang Yao, Shi Guo, Junhao Zhuang et al. · 0 citations
Jul 2026

RealVDeblur: One-Step Diffusion for Generalizable Real-World Video Deblurring

An efficient generative framework designed to improve in-the-wild robustness under diverse real capture conditions and demonstrate strong perceptual quality, semantic fidelity, and temporal consistency on unseen videos, as well as improved robustness in downstream 3D reconstruction under severe motion blur.

Renbiao Jin, Ming-Hsuan Yang, Yutian Chen et al. · 0 citations

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