7 citations · 21 across the 7 of their papers we have counts for
4 papers · 1 filter
Deriving Commonsense Inference Tasks from Interactive Fictions
Mo Yu, Xiaoxiao Guo, Yufei Feng +3
Commonsense reasoning simulates the human ability to make presumptions about our physical world, and it is an indispensable cornerstone in building general AI systems. We propose a…
TED: Teaching AI to Explain its Decisions
Michael Hind, Dennis Wei, Murray Campbell +5
Artificial intelligence systems are being increasingly deployed due to their potential to increase the efficiency, scale, consistency, fairness, and accuracy of decisions. However,…
Teaching Meaningful Explanations
Noel C. F. Codella, Michael Hind, Karthikeyan Natesan Ramamurthy +5
The adoption of machine learning in high-stakes applications such as healthcare and law has lagged in part because predictions are not accompanied by explanations comprehensible to…
The Eigenoption-Critic Framework
Miao Liu, Marlos C. Machado, Gerald Tesauro +1
Eigenoptions (EOs) have been recently introduced as a promising idea for generating a diverse set of options through the graph Laplacian, having been shown to allow efficient explo…