From the 1 of 5 linked papers with an AI index.
5 papers
What Does It Mean to Break a Distillation Defense?
Lena Libon, Pura Peetathawatchai, Michael Aerni +2
The paper examines how to evaluate defenses that add noise to large language model outputs to thwart distillation attacks, proposing a three‑dimensional threat model (query budget,…
Large-scale online deanonymization with LLMs
Simon Lermen, Daniel Paleka, Joshua Swanson +3
We show that large language models can be used to perform at-scale deanonymization. With full Internet access, our agent can re-identify Hacker News users and Anthropic Interviewer…
Modal Aphasia: Can Unified Multimodal Models Describe Images From Memory?
Michael Aerni, Joshua Swanson, Kristina NikoliÄ +1
We present modal aphasia, a systematic dissociation in which current unified multimodal models accurately memorize concepts visually but fail to articulate them in writing, despite…
Apertus: Democratizing Open and Compliant LLMs for Global Language Environments
Project Apertus, Alejandro Hernández-Cano, Alexander Hägele +100
We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingu…
Membership Inference Attacks on Sequence Models
Lorenzo Rossi, Michael Aerni, Jie Zhang +1
Sequence models, such as Large Language Models (LLMs) and autoregressive image generators, have a tendency to memorize and inadvertently leak sensitive information. While this tend…