Fang Wu

Agent experience, even when uniformly unrewarded, can be distilled into predictive foresight to dramatically improve learning in sparse reward settings.

Multimodal models can achieve significant image generation improvements by learning from their own critiques during test-time compute, effectively acting as their own recursive self-improvement mechanism.