3 citations · 7 across the 10 of their papers we have counts for
5 papers · 1 filter
Watermark Anything with Localized Messages
Tom Sander, Pierre Fernandez, Alain Durmus +2
Image watermarking methods are not tailored to handle small watermarked areas. This restricts applications in real-world scenarios where parts of the image may come from different…
Log-normal Mutations and their Use in Detecting Surreptitious Fake Images
Ismail Labiad, Thomas Bäck, Pierre Fernandez +5
In many cases, adversarial attacks are based on specialized algorithms specifically dedicated to attacking automatic image classifiers. These algorithms perform well, thanks to an…
Differentially Private Representation Learning via Image Captioning
Tom Sander, Yaodong Yu, Maziar Sanjabi +4
Differentially private (DP) machine learning is considered the gold-standard solution for training a model from sensitive data while still preserving privacy. However, a major barr…
Implicit Bias in Noisy-SGD: With Applications to Differentially Private Training
Tom Sander, Maxime Sylvestre, Alain Durmus
Training Deep Neural Networks (DNNs) with small batches using Stochastic Gradient Descent (SGD) yields superior test performance compared to larger batches. The specific noise stru…
Watermarking Makes Language Models Radioactive
Tom Sander, Pierre Fernandez, Alain Durmus +2
We investigate the radioactivity of text generated by large language models (LLM), i.e. whether it is possible to detect that such synthetic input was used to train a subsequent LL…