11 papers
Medical Model Synthesis Architectures: A Case Study
Katherine M. Collins, Marlene Berke, Ilia Sucholutsky +6
Medicine is rife with high-stakes uncertainty. Doctors routinely make clinical judgments and decisions that juggle many fundamental unknowns, like predictions about what might be c…
Reason to Play: Behavioral and Brain Alignment Between Frontier LRMs and Human Game Learners
Botos Csaba, Sreejan Kumar, Austin Tudor David Andrews +6
Humans rapidly learn abstract knowledge when encountering novel environments and flexibly deploy this knowledge to guide efficient and intelligent action. Can modern AI systems lea…
A Matter of Interest: Understanding Interestingness of Math Problems in Humans and Language Models
Shubhra Mishra, Yuka Machino, Gabriel Poesia +9
The evolution of mathematics is shaped importantly by interestingness: researchers choose which problems to pursue, and students choose which problems to engage with, based on expe…
Code-enabled language models can outperform reasoning models on diverse tasks
Cedegao E. Zhang, Cédric Colas, Gabriel Poesia +2
Reasoning models (RMs), language models (LMs) trained with reinforcement learning to produce long-form natural language reasoning, have been remarkably successful, but they still r…
Shoot First, Ask Questions Later? Building Rational Agents that Explore and Act Like People
Gabriel Grand, Valerio Pepe, Jacob Andreas +1
Many emerging applications of AI--from scientific discovery to medical diagnosis--require agents to seek information strategically: forming hypotheses, asking targeted questions, a…
People use fast and flat simulation to reason about new games
Katherine M. Collins, Cedegao E. Zhang, Lionel Wong +6
Games have long been a microcosm for studying planning and reasoning in both natural and artificial intelligence (AI), often focusing on expert-level or even super-human play. But…
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…
On the Same Wavelength? Evaluating Pragmatic Reasoning in Language Models across Broad Concepts
Linlu Qiu, Cedegao E. Zhang, Joshua B. Tenenbaum +2
Language use is shaped by pragmatics -- i.e., reasoning about communicative goals and norms in context. As language models (LMs) are increasingly used as conversational agents, it…
Generation and Evaluation in the Human Invention Process through the Lens of Game Design
Katherine M. Collins, Graham Todd, Cedegao E. Zhang +6
The human ability to learn rules and solve problems has been a central concern of cognitive science research since the field's earliest days. But we do not just follow rules and so…
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…
Self-Steering Language Models
Gabriel Grand, Joshua B. Tenenbaum, Vikash K. Mansinghka +2
While test-time reasoning enables language models (LMs) to tackle complex tasks, searching or planning in natural language can be slow, costly, and error-prone. But even when LMs s…