574 citations · 2.1k across the 81 of their papers we have counts for
89 papers
The Universal Law of Generalization Holds for Naturalistic Stimuli
Raja Marjieh, Nori Jacoby, Joshua C. Peterson +1
Shepard's universal law of generalization is a remarkable hypothesis about how intelligent organisms should perceive similarity. In its broadest form, the universal law states that…
Modeling rapid language learning by distilling Bayesian priors into artificial neural networks
R. Thomas McCoy, Thomas L. Griffiths
Humans can learn languages from remarkably little experience. Developing computational models that explain this ability has been a major challenge in cognitive science. Bayesian mo…
Gaussian Process Probes (GPP) for Uncertainty-Aware Probing
Zi Wang, Alexander Ku, Jason Baldridge +2
Understanding which concepts models can and cannot represent has been fundamental to many tasks: from effective and responsible use of models to detecting out of distribution data.…
Im-Promptu: In-Context Composition from Image Prompts
Bhishma Dedhia, Michael Chang, Jake C. Snell +2
Large language models are few-shot learners that can solve diverse tasks from a handful of demonstrations. This implicit understanding of tasks suggests that the attention mechanis…
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Shunyu Yao, Dian Yu, Jeffrey Zhao +4
Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making proce…
Superhuman Artificial Intelligence Can Improve Human Decision Making by Increasing Novelty
Minkyu Shin, Jin Kim, Bas van Opheusden +1
How will superhuman artificial intelligence (AI) affect human decision making? And what will be the mechanisms behind this effect? We address these questions in a domain where AI a…