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cs.LG2026
Couple to Control: Joint Initial Noise Design in Diffusion Models
Jing Jia, Liyue Shen, Guanyang Wang
Diffusion models typically generate image batches from independent Gaussian initial noises. We argue that this independence assumption is only one choice within a broader class of…
cs.LG2025
Antithetic Noise in Diffusion Models
Jing Jia, Sifan Liu, Bowen Song +3
We systematically study antithetic initial noise in diffusion models, discovering that pairing each noise sample with its negation consistently produces strong negative correlation…
cs.LG2025
CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation
Bowen Song, Zecheng Zhang, Zhaoxu Luo +6
Diffusion models have emerged as powerful tools for generative tasks, producing high-quality outputs across diverse domains. However, how the generated data responds to the initial…