2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CL2020★ 2 cited
QUACKIE: A NLP Classification Task With Ground Truth Explanations
Yves Rychener, Xavier Renard, Djamé Seddah +2
NLP Interpretability aims to increase trust in model predictions. This makes evaluating interpretability approaches a pressing issue. There are multiple datasets for evaluating NLP…
cs.CL2020★ 1 cited
On the Granularity of Explanations in Model Agnostic NLP Interpretability
Yves Rychener, Xavier Renard, Djamé Seddah +2
Current methods for Black-Box NLP interpretability, like LIME or SHAP, are based on altering the text to interpret by removing words and modeling the Black-Box response. In this pa…