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Explainability
ServiceNow Research
Explainability
Explainable, Sensible and Virtuous Workplace Chatbots
We outline three research directions towards the practical implementation of explainable, sensible and virtuous chatbots for the …
Gabriel Huang
,
Valérie Bécaert
,
David Vazquez
Montreal AI Symposium (MAIS), 2022.
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Explaining by Example: A Practitioner’s Perspective
Black-box machine learning (ML) models have become increasingly popular in practice. They can offer great performance, especially in …
Marc-Etienne Brunet
,
Masoud Hashemi
Montreal AI Symposium (MAIS), 2022.
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Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations
Explainability for machine learning models has gained considerable attention within the research community given the importance of …
Pau Rodriguez
,
Massimo Caccia
,
Alexandre Lacoste
,
Lee Zamparo
,
Issam H. Laradji
,
Laurent Charlin
,
David Vazquez
International Conference on Computer Vision (ICCV), 2021.
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RelatIF: Identifying Explanatory Training Examples via Relative Influence
In this work, we focus on the use of influence functions to identify relevant training examples that one might hope …
Elnaz Barshan
,
Marc-Etienne Brunet
,
Gintare Karolina Dziugaite
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
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