18 citations · 46 across the 25 of their papers we have counts for
8 papers · 1 filter
A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing
Jared Moore, Noah Goodman, Nick Haber +1
Large language models can shift human beliefs across high-stakes domains, but most persuasion studies rely on pre/post belief change. These endpoint measures identify whether persu…
How LLMs Distort Our Written Language
Marwa Abdulhai, Isadora White, Yanming Wan +4
Large language models (LLMs) are used by over a billion people globally, most often to assist with writing. In this work, we demonstrate that LLMs not only alter the voice and tone…
Generative Value Conflicts Reveal LLM Priorities
Andy Liu, Kshitish Ghate, Mona Diab +3
Past work seeks to align large language model (LLM)-based assistants with a target set of values, but such assistants are frequently forced to make tradeoffs between values when de…
Are Language Models Consequentialist or Deontological Moral Reasoners?
Keenan Samway, Max Kleiman-Weiner, David Guzman Piedrahita +3
As AI systems increasingly navigate applications in healthcare, law, and governance, understanding how they handle ethically complex scenarios becomes critical. Previous work has m…
SafetyAnalyst: Interpretable, Transparent, and Steerable Safety Moderation for AI Behavior
Jing-Jing Li, Valentina Pyatkin, Max Kleiman-Weiner +7
The ideal AI safety moderation system would be both structurally interpretable (so its decisions can be reliably explained) and steerable (to align to safety standards and reflect…
Language Model Alignment in Multilingual Trolley Problems
Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti +9
We evaluate the moral alignment of LLMs with human preferences in multilingual trolley problems. Building on the Moral Machine experiment, which captures over 40 million human judg…