90 citations · 110 across the 10 of their papers we have counts for
5 papers · 1 filter
Detecting CSAM Text-to-Image LoRAs From Weights
David Demitri Africa, Cate Heine, Nadine Staes-Polet +1
Low-rank adaptation (LoRA) fine-tuning has made it cheap and easy to customize open-weight image generation models for specific tasks, including the production of child sexual abus…
SoK: Data Minimization in Machine Learning
Robin Staab, Nikola Jovanović, Kimberly Mai +4
Data minimization (DM) describes the principle of collecting only the data strictly necessary for a given task. It is a foundational principle across major data protection regulati…
An Example Safety Case for Safeguards Against Misuse
Joshua Clymer, Jonah Weinbaum, Robert Kirk +3
Existing evaluations of AI misuse safeguards provide a patchwork of evidence that is often difficult to connect to real-world decisions. To bridge this gap, we describe an end-to-e…
Understanding the limitations of self-supervised learning for tabular anomaly detection
Kimberly T. Mai, Toby Davies, Lewis D. Griffin
While self-supervised learning has improved anomaly detection in computer vision and natural language processing, it is unclear whether tabular data can benefit from it. This paper…
Brittle Features May Help Anomaly Detection
Kimberly T. Mai, Toby Davies, Lewis D. Griffin
One-class anomaly detection is challenging. A representation that clearly distinguishes anomalies from normal data is ideal, but arriving at this representation is difficult since…