activity
20222025
most citedProactive Detection of Voice Cloning with Localized Watermarking

7 citations · 12 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2025

Task-Agnostic Attacks Against Vision Foundation Models

Brian Pulfer, Yury Belousov, Vitaliy Kinakh +2

The study of security in machine learning mainly focuses on downstream task-specific attacks, where the adversarial example is obtained by optimizing a loss function specific to th…

cs.CV2024★ 1 cited

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…

cs.CV2024

Evaluation of Security of ML-based Watermarking: Copy and Removal Attacks

Vitaliy Kinakh, Brian Pulfer, Yury Belousov +3

The vast amounts of digital content captured from the real world or AI-generated media necessitate methods for copyright protection, traceability, or data provenance verification.…

cs.CR2024★ 3 cited

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…

cs.SD2024★ 7 cited

Proactive Detection of Voice Cloning with Localized Watermarking

Robin San Roman, Pierre Fernandez, Alexandre Défossez +3

In the rapidly evolving field of speech generative models, there is a pressing need to ensure audio authenticity against the risks of voice cloning. We present AudioSeal, the first…

cs.CR2023

Functional Invariants to Watermark Large Transformers

Pierre Fernandez, Guillaume Couairon, Teddy Furon +1

The rapid growth of transformer-based models increases the concerns about their integrity and ownership insurance. Watermarking addresses this issue by embedding a unique identifie…

cs.CR2022★ 1 cited

FBI: Fingerprinting models with Benign Inputs

Thibault Maho, Teddy Furon, Erwan Le Merrer

Recent advances in the fingerprinting of deep neural networks detect instances of models, placed in a black-box interaction scheme. Inputs used by the fingerprinting protocols are…