40 citations · 77 across the 7 of their papers we have counts for
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cs.LG2021★ 40 cited
Machine Learning Practices Outside Big Tech: How Resource Constraints Challenge Responsible Development
Aspen Hopkins, Serena Booth
Practitioners from diverse occupations and backgrounds are increasingly using machine learning (ML) methods. Nonetheless, studies on ML Practitioners typically draw populations fro…
cs.CL2021★ 5 cited
The Irrationality of Neural Rationale Models
Yiming Zheng, Serena Booth, Julie Shah +1
Neural rationale models are popular for interpretable predictions of NLP tasks. In these, a selector extracts segments of the input text, called rationales, and passes these segmen…
cs.LG2021★ 16 cited
Do Feature Attribution Methods Correctly Attribute Features?
Yilun Zhou, Serena Booth, Marco Tulio Ribeiro +1
Feature attribution methods are popular in interpretable machine learning. These methods compute the attribution of each input feature to represent its importance, but there is no…