Yunpeng Chen

Generation-first training eliminates latent collapse, achieving unprecedented stability and performance in latent generative modeling.

Reinforcement learning boosts multimodal performance, raising task scores and creating unexpected synergies between image generation and editing.

A reward model trained on spatial relationship preferences beats proprietary models at spatial understanding in text-to-image generation, and unlocks better RL-based image generation.