Learning Native Reflection in Unified Models with Interleaved Reinforcement Learning

Summary

This paper presents UMM-Reflection, a method that teaches unified multimodal models to critique and fix their own image generations through reinforcement learning. Instead of just generating images once, the model can now look at what it created, identify problems, revise the image, and repeat—all within a single model.