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Evolving generative models in residual space reveals a powerful balance between local refinement and global exploration, enhancing data editing capabilities.
Offline RL can now refine trajectories conservatively without risking extrapolation, thanks to a novel framework that leverages local preference pairs for targeted improvements.
