collaborators

18 papers

cs.AI2026

Activation Steering for Aligned Open-ended Generation without Sacrificing Coherence

Niklas Herbster, Martin Zborowski, Alberto Tosato +2

Alignment in LLMs is more brittle than commonly assumed: misalignment can be induced by adversarial prompts, benign fine-tuning, emergent misalignment, and goal misgeneralization.…

math.OC2026

Accelerated and Stable Convergence with Anchored Generalized Optimistic Method

Motahareh Sohrabi, Jianxin You, Simon Lacoste-Julien +2

We study first-order methods for solving monotone variational inequalities arising in min-max optimization. Classical approaches such as the extragradient method rely on two gradie…

cs.CR2026

LLM-Safety Evaluations Lack Robustness

Tim Beyer, Sophie Xhonneux, Simon Geisler +3

In this paper, we argue that current safety alignment research efforts for large language models are hindered by many intertwined sources of noise, such as small datasets, methodol…

cs.GT2026

Why Open Source? A Game-Theoretic Analysis of the AI Race

Andjela Mladenovic, Aaron Courville, Gauthier Gidel

In recent years, with the advancement of frontier AI, we have observed certain dynamics in open-sourcing and closed-sourcing decisions. We propose a game-theoretic model to analyze…

cs.CL2026

A Coin Flip for Safety: LLM Judges Fail to Reliably Measure Adversarial Robustness

Leo Schwinn, Moritz Ladenburger, Tim Beyer +3

Automated \enquote{LLM-as-a-Judge} frameworks have become the de facto standard for scalable evaluation across natural language processing. For instance, in safety evaluation, thes…

stat.ML2026

Logarithmic-time Schedules for Scaling Language Models with Momentum

Damien Ferbach, Courtney Paquette, Gauthier Gidel +2

In practice, the hyperparameters and weight-decay in AdamW are typically kept at fixed values. Is there any reason to do otherwise? We show that for large-scale…