Watermarking in Generative AI

We study generative AI watermarking, identifying novel vulnerabilities in existing systems and developing new systems for ensuring provenance of generative model outputs, weights, and training data.

Blog Posts

Probing Google DeepMind's SynthID-Text Watermark

We apply the techniques from our recent work to investigate how SynthID-Text, the first large-scale deployment of an LLM watermarking scheme, fares in several adversarial scenarios.

Publications

2025

Transferable Black-Box One-Shot Forging of Watermarks via Image Preference Models

Tomas Soucek, Sylvestre-Alvise Rebuffi, Pierre Fernandez, Nikola Jovanović, Hady Elsahar, Valeriu Lacatusu, Tuan A. Tran, Alexandre Mourachko

NeurIPS 2025 Spotlight

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Watermarking Autoregressive Image Generation

Nikola Jovanović, Ismail Labiad, Tomáš Souček, Martin Vechev, Pierre Fernandez

NeurIPS 2025

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Watermarking Diffusion Language Models

Thibaud Gloaguen, Robin Staab, Nikola Jovanović, Martin Vechev

GenProCC @ NeurIPS 2025 2025

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Geometric Image Synchronization with Deep Watermarking

Pierre Fernandez, Tomáš Souček, Nikola Jovanović, Hady Elsahar, Sylvestre-Alvise Rebuffi, Valeriu Lacatusu, Tuan Tran, Alexandre Mourachko

arXiv 2025

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Discovering Spoofing Attempts on Language Model Watermarks

Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev

ICML 2025

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Robust LLM Fingerprinting via Domain-Specific Watermarks

Thibaud Gloaguen, Robin Staab, Nikola Jovanović and Martin Vechev

arXiv 2025

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Ward: Provable RAG Dataset Inference via LLM Watermarks

Nikola Jovanović, Robin Staab, Maximilian Baader, Martin Vechev

ICLR 2025

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Towards Watermarking of Open-Source LLMs

Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev

WMARK @ ICLR 2025

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Black-Box Detection of Language Model Watermarks

Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev

ICLR 2025

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2024

Watermark Stealing in Large Language Models

Nikola Jovanović, Robin Staab, Martin Vechev

ICML 2024 R2-FM@ICLR24 Oral

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