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Training Data Attribution in Diffusion Models via Mirrored Unlearning and Noise-Consistent Skew
MUCS improves diffusion model training data attribution via mirrored unlearning and noise-consistent skew, outperforming existing methods across datasets.
Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026
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AI panel: 14 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 1/5