@inproceedings{kamp-etal-2024-role-syntactic,
title = "The Role of Syntactic Span Preferences in Post-Hoc Explanation Disagreement",
author = "Kamp, Jonathan and
Beinborn, Lisa and
Fokkens, Antske",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.1397",
pages = "16066--16078",
abstract = "Post-hoc explanation methods for transformer models tend to disagree with one another. Agreement is generally measured for a small subset of most important tokens. However, the presence of disagreement is often overlooked and the reasons for disagreement insufficiently examined, causing these methods to be utilised without adequate care. In this work, we explain disagreement from a linguistic perspective. We find that different methods systematically select different token types. Additionally, similar methods display similar linguistic preferences, which consequently affect agreement. By estimating the subsets of *k* most important tokens dynamically over sentences, we find that methods better agree on the syntactic span level. Especially the methods that agree the least with other methods benefit most from this dynamic subset estimation. We methodically explore the different settings of the dynamic *k* approach: we observe that its combination with spans yields favourable results in capturing important signals in the sentence, and propose an improved setting of global token importance.",
}
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<abstract>Post-hoc explanation methods for transformer models tend to disagree with one another. Agreement is generally measured for a small subset of most important tokens. However, the presence of disagreement is often overlooked and the reasons for disagreement insufficiently examined, causing these methods to be utilised without adequate care. In this work, we explain disagreement from a linguistic perspective. We find that different methods systematically select different token types. Additionally, similar methods display similar linguistic preferences, which consequently affect agreement. By estimating the subsets of *k* most important tokens dynamically over sentences, we find that methods better agree on the syntactic span level. Especially the methods that agree the least with other methods benefit most from this dynamic subset estimation. We methodically explore the different settings of the dynamic *k* approach: we observe that its combination with spans yields favourable results in capturing important signals in the sentence, and propose an improved setting of global token importance.</abstract>
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%0 Conference Proceedings
%T The Role of Syntactic Span Preferences in Post-Hoc Explanation Disagreement
%A Kamp, Jonathan
%A Beinborn, Lisa
%A Fokkens, Antske
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F kamp-etal-2024-role-syntactic
%X Post-hoc explanation methods for transformer models tend to disagree with one another. Agreement is generally measured for a small subset of most important tokens. However, the presence of disagreement is often overlooked and the reasons for disagreement insufficiently examined, causing these methods to be utilised without adequate care. In this work, we explain disagreement from a linguistic perspective. We find that different methods systematically select different token types. Additionally, similar methods display similar linguistic preferences, which consequently affect agreement. By estimating the subsets of *k* most important tokens dynamically over sentences, we find that methods better agree on the syntactic span level. Especially the methods that agree the least with other methods benefit most from this dynamic subset estimation. We methodically explore the different settings of the dynamic *k* approach: we observe that its combination with spans yields favourable results in capturing important signals in the sentence, and propose an improved setting of global token importance.
%U https://aclanthology.org/2024.lrec-main.1397
%P 16066-16078
Markdown (Informal)
[The Role of Syntactic Span Preferences in Post-Hoc Explanation Disagreement](https://aclanthology.org/2024.lrec-main.1397) (Kamp et al., LREC-COLING 2024)
ACL