24 citations · 48 across the 10 of their papers we have counts for
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cs.CL2020
Explaining NLP Models via Minimal Contrastive Editing (MiCE)
Alexis Ross, Ana Marasović, Matthew E. Peters
Humans have been shown to give contrastive explanations, which explain why an observed event happened rather than some other counterfactual event (the contrast case). Despite the i…
cs.LG2020
Learning Models for Actionable Recourse
Alexis Ross, Himabindu Lakkaraju, Osbert Bastani
As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for gen…