Can We Perform Online RL for Image Editing without Editing Rewards?
Lever-Edit is introduced, a two-stage framework that learns a reward-aligned captioner for counterfactual target descriptions, freezes it, and optimizes the editing policy solely with the transferred T2I reward, showing competitive editing alignment and source preservation against editing-reward-based fine-tuning, whil...