Khoa D Doan

Current depression patient simulators are more like Pollyannas than patients, resolving negative emotions too quickly and following a predictable trajectory from negative to positive.

CLIP models suffer from a surprisingly strong "center bias," causing them to miss important objects outside the image's central region, even when those objects are crucial for accurate vision-language understanding.

LRMs can often recover from injected errors in their reasoning steps, revealing a hidden "critique" ability that can be harnessed to improve performance without additional training.