Zuxuan Wu

VA-Judger transforms reward modeling by integrating human preference feedback, leading to coherent and high-quality video-audio generation that outperforms traditional metrics.

Semantic visual-action tokenization in RepWAM significantly enhances robotic manipulation performance, outperforming traditional reconstruction-based approaches.

Aligning shallow and deep features in representation autoencoders leads to a dramatic improvement in image reconstruction quality, setting new benchmarks in the field.