Citation

BibTex format

@inproceedings{Lertvittayakumjorn,
author = {Lertvittayakumjorn, P and Toni, F},
publisher = {ACL Anthology},
title = {Human-grounded evaluations of explanation methods for text classification},
url = {https://www.aclweb.org/anthology/},
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - Due to the black-box nature of deep learning models, methods for explaining the models’ results are crucial to gain trust from humans and support collaboration between AIsand humans. In this paper, we consider several model-agnostic and model-specific explanation methods for CNNs for text classification and conduct three human-grounded evaluations, focusing on different purposes of explanations: (1) revealing model behavior, (2)justifying model predictions, and (3) helping humans investigate uncertain predictions.The results highlight dissimilar qualities of thevarious explanation methods we consider andshow the degree to which these methods couldserve for each purpose.
AU - Lertvittayakumjorn,P
AU - Toni,F
PB - ACL Anthology
TI - Human-grounded evaluations of explanation methods for text classification
UR - https://www.aclweb.org/anthology/
UR - http://hdl.handle.net/10044/1/73206
ER -