1 citations · 1 across the 6 of their papers we have counts for
4 papers · 1 filter
The Pain Axis: LLMs Represent Self-Directed Harm and Act on It
Valen Tagliabue, Leonard Dung, Cameron Berg
LLMs sometimes behave in ways resembling human emotional responses, and recent work identified internal representations that may underlie these behaviors. We ask whether LLMs repre…
Instrumental Choices: Measuring the Propensity of LLM Agents to Pursue Instrumental Behaviors
Jonas Wiedermann-Möller, Leonard Dung, Maksym Andriushchenko
AI systems have become increasingly capable of dangerous behaviours in many domains. This raises the question: Do models sometimes choose to violate human instructions in order to…
AI Alignment Strategies from a Risk Perspective: Independent Safety Mechanisms or Shared Failures?
Leonard Dung, Florian Mai
AI alignment research aims to develop techniques to ensure that AI systems do not cause harm. However, every alignment technique has failure modes, which are conditions in which th…
Probing the Preferences of a Language Model: Integrating Verbal and Behavioral Tests of AI Welfare
Valen Tagliabue, Leonard Dung
We develop new experimental paradigms for measuring welfare in language models. We compare verbal reports of models about their preferences with preferences expressed through behav…