arXiv Machine Learning June 9, 2026 By Kostas Triaridis, Alexandros Graikos, Aggelina Chatziagapi, Grigorios G. Chrysos, Dimitris Samaras

Mitigating Diffusion Model Hallucinations with Dynamic Guidance

Read the original on arXiv Machine Learning →

arXiv:2510. 05356v2 Announce Type: replace-cross Abstract: Hallucinations in diffusion models are samples with structural inconsistencies that can emerge due to the excessive smoothing of the learned score function, which in turn leads to interpolations between modes of the data distribution.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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