Yizheng Wu

Bridging the gap between synthetic and real-world motion prediction, this framework achieves superior performance by leveraging objectness priors to refine motion labels.

VLMs reason better when shown visually similar examples with synonymous questions, enabling a new self-training approach that beats state-of-the-art visual reasoning datasets.