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Forget GAN inversions – now you can steer diffusion models with a dynamically weighted soup of differentiable rewards, including a VQA-based reward for language-vision reasoning, and get SOTA image edits.
Full gradient updates can stabilize successor feature learning, unlocking more effective transfer in RL.
