From the 2 of 19 linked papers with an AI index.
1 citations · 2 across the 6 of their papers we have counts for
6 papers · 1 filter
Post-training makes large language models less human-like
Marcel Binz, Elif Akata, Abdullah Almaatouq +76
Large language models (LLMs) are increasingly used as surrogates for human participants, but it remains unclear which models best capture human behavior and why. To address this, w…
Evaluating Language Models' Evaluations of Games
Katherine M. Collins, Cedegao E. Zhang, Graham Todd +9
Reasoning is not just about solving problems -- it is also about evaluating which problems are worth solving at all. Evaluations of artificial intelligence (AI) systems primarily f…
Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models
Lionel Wong, Katherine M. Collins, Lance Ying +8
When faced with novel situations, people are able to marshal relevant considerations from a wide range of background knowledge and put these to use in inferences and predictions. W…
Language-Informed Synthesis of Rational Agent Models for Grounded Theory-of-Mind Reasoning On-The-Fly
Lance Ying, Ryan Truong, Katherine M. Collins +6
Drawing real world social inferences usually requires taking into account information from multiple modalities. Language is a particularly powerful source of information in social…
Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality
Lance Ying, Almog Hillel, Ryan Truong +3
A key feature of human theory-of-mind is the ability to attribute beliefs to other agents as mentalistic explanations for their behavior. But given the wide variety of beliefs that…
Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind
Lance Ying, Tan Zhi-Xuan, Lionel Wong +2
How do people understand and evaluate claims about others' beliefs, even though these beliefs cannot be directly observed? In this paper, we introduce a cognitive model of epistemi…