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cs.LG2026
Selective Timestep Weighting and Advantage-Based Replay for Sample-Efficient Diffusion RLHF
Eric Zhu, Abhinav Shrivastava, Soumik Mukhopadhyay
Reinforcement learning from human feedback (RLHF) has emerged as a powerful paradigm for aligning generative models with human preferences. However, applying RLHF to diffusion mode…
cs.LG2023★ 1 cited
Diffusion on the Probability Simplex
Griffin Floto, Thorsteinn Jonsson, Mihai Nica +2
Diffusion models learn to reverse the progressive noising of a data distribution to create a generative model. However, the desired continuous nature of the noising process can be…