Yi Wan

CFR-Net outperforms traditional models in medical image anomaly detection by refining features collaboratively, even when trained only on normal data.

Multimodal models struggle to keep up with our ever-changing world: SFT and RLHF catastrophically forget, while knowledge editing falters at continual learning, as shown by the new MMKU-Bench benchmark.