AI RESEARCH
Query Lower Bounds for Diffusion Sampling
arXiv CS.AI
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ArXi:2604.10857v1 Announce Type: cross Diffusion models generate samples by iteratively querying learned score estimates. A rapidly growing literature focuses on accelerating sampling by minimizing the number of score evaluations, yet the information-theoretic limits of such acceleration remain unclear. In this work, we establish the first score query lower bounds for diffusion sampling.