Andi Zhang

Adversarial training gains a principled probabilistic interpretation and improved robustness via KL divergence maximization, outperforming standard methods.

Information density imbalance, not just instance count, is a key driver of category bias in object detection models, revealing new avenues for enhancing fairness and accuracy.