1 citations · 2 across the 7 of their papers we have counts for
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You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models
Kairan Zhao, Eleni Triantafillou, Peter Triantafillou
Generative models have been shown to "memorize" certain training data, leading to verbatim or near-verbatim generating images, which may cause privacy concerns or copyright infring…
Benchmarking Unlearning for Vision Transformers
Kairan Zhao, Iurie Luca, Peter Triantafillou
Machine unlearning (MU) refers to the post-training capability to remove (the influence of) training examples that are incorrect, biased, or leak sensitive/private information. MU…
Localising Shortcut Learning in Pixel Space via Ordinal Scoring Correlations for Attribution Representations (OSCAR)
Akshit Achara, Peter Triantafillou, Esther Puyol-Antón +2
Deep neural networks often exploit shortcuts. These are spurious cues which are associated with output labels in the training data but are unrelated to task semantics. When the sho…