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arXiv Computer Vision By Lior Ziv, Mahmood Sharif

Haste Makes Waste? Towards Safe Few-Step Text-to-Image Models

Read the original on arXiv Computer Vision →

The paper investigates the safety implications of few-step distilled text-to-image models, finding that faster generation often leads to higher unsafe content rates and that existing concept-erasure methods are less effective on these models. The authors diagnose why erasure fails, attributing it to the fragile generation process and the way guidance is distilled. They propose DICE, a post-distillation erasure technique that aligns with the distillation process, achieving a significant reduction in unsafe-generation rates while preserving quality.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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