most citedTransforming Science Learning Materials in the Era of Artificial Intelligence

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cs.CV2026

Roots Beneath the Cut: Uncovering the Risk of Concept Revival in Pruning-Based Unlearning for Diffusion Models

Ci Zhang, Zhaojun Ding, Chence Yang +7

Pruning-based unlearning has recently emerged as a fast, training-free, and data-independent approach to remove undesired concepts from diffusion models. It promises high efficienc…