11 papers
AI Assistants Overassist
Verona Teo, Raghav Jain, Tobias Gerstenberg +1
Large language models (LLMs) are increasingly used as tutors and thought partners, helping users reason through problems. While guidance from AI assistants can scaffold thinking an…
A Communication-First Account of Explanation
Jacqueline Harding, Tobias Gerstenberg, Thomas Icard
This paper develops a formal account of causal explanation, grounded in a theory of conversational pragmatics, and inspired by the interventionist idea that explanation is about as…
Effective Explanations Support Planning Under Uncertainty
Hanqi Zhou, Britt Besch, Charley M. Wu +1
Explaining how to get from A to B can be challenging. It requires mentally simulating what the listener will do based on what they are told. To capture this process, we propose a c…
Why Someone Asked "Why": Foil Inference in Human and LLM Question Interpretation
Britt Besch, Tobias Gerstenberg
Explanations are inherently contrastive: E happened rather than E' because of C rather than C'. However, these contrasts, or "foils", are rarely mentioned explicitly but have to be…
Human-like Affective Cognition in Foundation Models
Kanishk Gandhi, Zoe Lynch, Jan-Philipp Fränken +5
Understanding emotions is fundamental to human interaction and experience. Humans easily infer emotions from situations or facial expressions, situations from emotions, and do a va…
From Retrieving Information to Reasoning with AI: Exploring Different Interaction Modalities to Support Human-AI Coordination in Clinical Decision-Making
Behnam Rahdari, Sameer Shaikh, Jonathan H Chen +2
LLMs are popular among clinicians for decision-support because of simple text-based interaction. However, their impact on clinicians' performance is ambiguous. Not knowing how clin…