198 citations · 234 across the 9 of their papers we have counts for
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cs.CL2021★ 3 cited
Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining
Andreas Madsen, Nicholas Meade, Vaibhav Adlakha +1
To explain NLP models a popular approach is to use importance measures, such as attention, which inform input tokens are important for making a prediction. However, an open questio…
cs.CL2021★ 198 cited
Post-hoc Interpretability for Neural NLP: A Survey
Andreas Madsen, Siva Reddy, Sarath Chandar
Neural networks for NLP are becoming increasingly complex and widespread, and there is a growing concern if these models are responsible to use. Explaining models helps to address…