Considering Likelihood in NLP Classification Explanations with Occlusion and Language Modeling

21 April 2020

Papers citing "Considering Likelihood in NLP Classification Explanations with Occlusion and Language Modeling"

4 / 4 papers shown

Title
XPASC: Measuring Generalization in Weak Supervision by Explainability and Association Luisa März Ehsaneddin Asgari Fabienne Braune Franziska Zimmermann Benjamin Roth 23 0 0 03 Jun 2022
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection Esma Balkir I. Nejadgholi Kathleen C. Fraser S. Kiritchenko FAtt 33 27 0 06 May 2022
Double Trouble: How to not explain a text classifier's decisions using counterfactuals synthesized by masked language models? Thang M. Pham Trung H. Bui Long Mai Anh Totti Nguyen 21 7 0 22 Oct 2021
Efficient Explanations from Empirical Explainers Robert Schwarzenberg Nils Feldhus Sebastian Möller FAtt 27 9 0 29 Mar 2021