5 citations · 10 across the 13 of their papers we have counts for
5 papers · 2 filters
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…
Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models
Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi +3
Language models (LMs) are increasingly used to simulate human-like responses in scenarios where accurately mimicking a population's behavior can guide decision-making, such as in d…
Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels
Jan-Philipp Fränken, Eric Zelikman, Rafael Rafailov +3
When prompting a language model (LM), users often expect the model to adhere to a set of behavioral principles across diverse tasks, such as producing insightful content while avoi…
Procedural Dilemma Generation for Evaluating Moral Reasoning in Humans and Language Models
Jan-Philipp Fränken, Kanishk Gandhi, Tori Qiu +3
As AI systems like language models are increasingly integrated into decision-making processes affecting people's lives, it's critical to ensure that these systems have sound moral…
STaR-GATE: Teaching Language Models to Ask Clarifying Questions
Chinmaya Andukuri, Jan-Philipp Fränken, Tobias Gerstenberg +1
When prompting language models to complete a task, users often leave important aspects unsaid. While asking questions could resolve this ambiguity (GATE; Li et al., 2023), models o…