40 citations · 93 across the 10 of their papers we have counts for
5 papers · 1 filter
Emergent Analogical Reasoning in Large Language Models
Taylor Webb, Keith J. Holyoak, Hongjing Lu
The recent advent of large language models has reinvigorated debate over whether human cognitive capacities might emerge in such generic models given sufficient training data. Of p…
CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models
Arjun R. Akula, Keze Wang, Changsong Liu +5
We propose CX-ToM, short for counterfactual explanations with theory-of mind, a new explainable AI (XAI) framework for explaining decisions made by a deep convolutional neural netw…
Visual analogy: Deep learning versus compositional models
Nicholas Ichien, Qing Liu, Shuhao Fu +3
Is analogical reasoning a task that must be learned to solve from scratch by applying deep learning models to massive numbers of reasoning problems? Or are analogies solved by comp…
Probabilistic Analogical Mapping with Semantic Relation Networks
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 thei…
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust
Arjun R. Akula, Changsong Liu, Sari Saba-Sadiya +4
We present a new explainable AI (XAI) framework aimed at increasing justified human trust and reliance in the AI machine through explanations. We pose explanation as an iterative c…