1k citations · 1.3k across the 56 of their papers we have counts for
59 papers
No Safe Dose: How Training Data Drives Unsafe Image Generation
Felix Friedrich, Lukas Helff, Niharika Hegde +2
Text-to-image models trained on large-scale data often inevitably ingest unsafe content. While some people observe input-output amplifications, it remains unclear whether and how t…
Multilingual Steering by Design: Multilingual Sparse Autoencoders and Principled Layer Selection
Yusser Al Ghussin, Daniil Gurgurov, Tanja Baeumel +3
Sparse autoencoders (SAEs) enable feature-level mechanistic interpretability and activation steering in large language models (LLMs), but SAE-based language control remains unrelia…
SocialGrid: A Benchmark for Planning and Social Reasoning in Embodied Multi-Agent Systems
Hikaru Shindo, Hanzhao Lin, Lukas Helff +2
As Large Language Models (LLMs) transition from text processors to autonomous agents, evaluating their social reasoning in embodied multi-agent settings becomes critical. We introd…
LLMs Gaming Verifiers: RLVR can Lead to Reward Hacking
Lukas Helff, Quentin Delfosse, David Steinmann +6
As reinforcement Learning with Verifiable Rewards (RLVR) has become the dominant paradigm for scaling reasoning capabilities in LLMs, a new failure mode emerges: LLMs gaming verifi…
Breaking Up with Normatively Monolithic Agency with GRACE: A Reason-Based Neuro-Symbolic Architecture for Safe and Ethical AI Alignment
Felix Jahn, Yannic Muskalla, Lisa Dargasz +2
As AI agents become increasingly autonomous, widely deployed in consequential contexts, and efficacious in bringing about real-world impacts, ensuring that their decisions are not…
CLaS-Bench: A Cross-Lingual Alignment and Steering Benchmark
Daniil Gurgurov, Yusser Al Ghussin, Tanja Baeumel +5
Understanding and controlling the behavior of large language models (LLMs) is an increasingly important topic in multilingual NLP. Beyond prompting or fine-tuning, , i.e.,~manipula…