@inproceedings{jacovi-etal-2023-neighboring,
title = "Neighboring Words Affect Human Interpretation of Saliency Explanations",
author = "Jacovi, Alon and
Schuff, Hendrik and
Adel, Heike and
Vu, Ngoc Thang and
Goldberg, Yoav",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.750",
doi = "10.18653/v1/2023.findings-acl.750",
pages = "11816--11833",
abstract = "Word-level saliency explanations ({``}heat maps over words{''}) are often used to communicate feature-attribution in text-based models. Recent studies found that superficial factors such as word length can distort human interpretation of the communicated saliency scores. We conduct a user study to investigate how the marking of a word{'}s *neighboring words* affect the explainee{'}s perception of the word{'}s importance in the context of a saliency explanation. We find that neighboring words have significant effects on the word{'}s importance rating. Concretely, we identify that the influence changes based on neighboring direction (left vs. right) and a-priori linguistic and computational measures of phrases and collocations (vs. unrelated neighboring words).Our results question whether text-based saliency explanations should be continued to be communicated at word level, and inform future research on alternative saliency explanation methods.",
}
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<abstract>Word-level saliency explanations (“heat maps over words”) are often used to communicate feature-attribution in text-based models. Recent studies found that superficial factors such as word length can distort human interpretation of the communicated saliency scores. We conduct a user study to investigate how the marking of a word’s *neighboring words* affect the explainee’s perception of the word’s importance in the context of a saliency explanation. We find that neighboring words have significant effects on the word’s importance rating. Concretely, we identify that the influence changes based on neighboring direction (left vs. right) and a-priori linguistic and computational measures of phrases and collocations (vs. unrelated neighboring words).Our results question whether text-based saliency explanations should be continued to be communicated at word level, and inform future research on alternative saliency explanation methods.</abstract>
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%0 Conference Proceedings
%T Neighboring Words Affect Human Interpretation of Saliency Explanations
%A Jacovi, Alon
%A Schuff, Hendrik
%A Adel, Heike
%A Vu, Ngoc Thang
%A Goldberg, Yoav
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Findings of the Association for Computational Linguistics: ACL 2023
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F jacovi-etal-2023-neighboring
%X Word-level saliency explanations (“heat maps over words”) are often used to communicate feature-attribution in text-based models. Recent studies found that superficial factors such as word length can distort human interpretation of the communicated saliency scores. We conduct a user study to investigate how the marking of a word’s *neighboring words* affect the explainee’s perception of the word’s importance in the context of a saliency explanation. We find that neighboring words have significant effects on the word’s importance rating. Concretely, we identify that the influence changes based on neighboring direction (left vs. right) and a-priori linguistic and computational measures of phrases and collocations (vs. unrelated neighboring words).Our results question whether text-based saliency explanations should be continued to be communicated at word level, and inform future research on alternative saliency explanation methods.
%R 10.18653/v1/2023.findings-acl.750
%U https://aclanthology.org/2023.findings-acl.750
%U https://doi.org/10.18653/v1/2023.findings-acl.750
%P 11816-11833
Markdown (Informal)
[Neighboring Words Affect Human Interpretation of Saliency Explanations](https://aclanthology.org/2023.findings-acl.750) (Jacovi et al., Findings 2023)
ACL