1 code implementation • 14 Apr 2024 • Taylor Webb, Keith J. Holyoak, Hongjing Lu
We recently reported evidence that large language models are capable of solving a wide range of text-based analogy problems in a zero-shot manner, indicating the presence of an emergent capacity for analogical reasoning.
no code implementations • 3 Aug 2023 • Nicholas Ichien, Dušan Stamenković, Keith J. Holyoak
In addition, for several novel English poems GPT4 produced interpretations that were rated as excellent or good by a human literary critic.
2 code implementations • 19 Dec 2022 • Taylor Webb, Keith J. Holyoak, Hongjing Lu
In human cognition, this capacity is closely tied to an ability to reason by analogy.
no code implementations • 29 Sep 2022 • Taylor W. Webb, Shuhao Fu, Trevor Bihl, Keith J. Holyoak, Hongjing Lu
Human reasoning is grounded in an ability to identify highly abstract commonalities governing superficially dissimilar visual inputs.
no code implementations • 14 May 2021 • Nicholas Ichien, Qing Liu, Shuhao Fu, Keith J. Holyoak, Alan Yuille, Hongjing Lu
We compared human performance to that of two recent deep learning models (Siamese Network and Relation Network) directly trained to solve these analogy problems, as well as to that of a compositional model that assesses relational similarity between part-based representations.
no code implementations • 30 Mar 2021 • Hongjing Lu, Nicholas Ichien, Keith J. Holyoak
The human ability to flexibly reason using analogies with domain-general content depends on mechanisms for identifying relations between concepts, and for mapping concepts and their relations across analogs.