6 papers
A Unified Framework for LLM Watermarks
Thibaud Gloaguen, Robin Staab, Nikola Jovanović +1
LLM watermarks allow tracing AI-generated texts by inserting a detectable signal into their generated content. Recent works have proposed a wide range of watermarking algorithms, e…
Fewer Weights, More Problems: A Practical Attack on LLM Pruning
Kazuki Egashira, Robin Staab, Thibaud Gloaguen +2
Model pruning, i.e., removing a subset of model weights, has become a prominent approach to reducing the memory footprint of large language models (LLMs) during inference. Notably,…
Watermarking Diffusion Language Models
Thibaud Gloaguen, Robin Staab, Nikola Jovanović +1
We introduce the first watermark tailored for diffusion language models (DLMs), an emergent LLM paradigm able to generate tokens in arbitrary order, in contrast to standard autoreg…
LLM Fingerprinting via Semantically Conditioned Watermarks
Thibaud Gloaguen, Robin Staab, Nikola Jovanović +1
Most LLM fingerprinting methods teach the model to respond to a few fixed queries with predefined atypical responses (keys). This memorization often does not survive common deploym…
Towards Watermarking of Open-Source LLMs
Thibaud Gloaguen, Nikola Jovanović, Robin Staab +1
While watermarks for closed LLMs have matured and have been included in large-scale deployments, these methods are not applicable to open-source models, which allow users full cont…
Discovering Spoofing Attempts on Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab +1
LLM watermarks stand out as a promising way to attribute ownership of LLM-generated text. One threat to watermark credibility comes from spoofing attacks, where an unauthorized thi…