@inproceedings{dobrzeniecka-etal-2025-improving,
title = "Improving Causal Interventions in Amnesic Probing with Mean Projection or {LEACE}",
author = "Dobrzeniecka, Alicja and
Fokkens, Antske and
Sommerauer, Pia",
editor = "Che, Wanxiang and
Nabende, Joyce and
Shutova, Ekaterina and
Pilehvar, Mohammad Taher",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2025",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-acl.674/",
doi = "10.18653/v1/2025.findings-acl.674",
pages = "12981--12993",
ISBN = "979-8-89176-256-5",
abstract = "Amnesic probing is a technique used to examine the influence of specific linguistic information on the behaviour of a model. This involves identifying and removing the relevant information and then assessing whether the model{'}s performance on the main task changes. If the removed information is relevant, the model{'}s performance should decline. The difficulty with this approach lies in removing \textit{only} the target information while leaving other information unchanged. It has been shown that Iterative Nullspace Projection (INLP), a widely used removal technique, introduces random modifications to representations when eliminating target information. We demonstrate that Mean Projection (MP) and LEACE, two proposed alternatives, remove information in a more targeted manner, thereby enhancing the potential for obtaining behavioural explanations through Amnesic Probing."
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<abstract>Amnesic probing is a technique used to examine the influence of specific linguistic information on the behaviour of a model. This involves identifying and removing the relevant information and then assessing whether the model’s performance on the main task changes. If the removed information is relevant, the model’s performance should decline. The difficulty with this approach lies in removing only the target information while leaving other information unchanged. It has been shown that Iterative Nullspace Projection (INLP), a widely used removal technique, introduces random modifications to representations when eliminating target information. We demonstrate that Mean Projection (MP) and LEACE, two proposed alternatives, remove information in a more targeted manner, thereby enhancing the potential for obtaining behavioural explanations through Amnesic Probing.</abstract>
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%0 Conference Proceedings
%T Improving Causal Interventions in Amnesic Probing with Mean Projection or LEACE
%A Dobrzeniecka, Alicja
%A Fokkens, Antske
%A Sommerauer, Pia
%Y Che, Wanxiang
%Y Nabende, Joyce
%Y Shutova, Ekaterina
%Y Pilehvar, Mohammad Taher
%S Findings of the Association for Computational Linguistics: ACL 2025
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-256-5
%F dobrzeniecka-etal-2025-improving
%X Amnesic probing is a technique used to examine the influence of specific linguistic information on the behaviour of a model. This involves identifying and removing the relevant information and then assessing whether the model’s performance on the main task changes. If the removed information is relevant, the model’s performance should decline. The difficulty with this approach lies in removing only the target information while leaving other information unchanged. It has been shown that Iterative Nullspace Projection (INLP), a widely used removal technique, introduces random modifications to representations when eliminating target information. We demonstrate that Mean Projection (MP) and LEACE, two proposed alternatives, remove information in a more targeted manner, thereby enhancing the potential for obtaining behavioural explanations through Amnesic Probing.
%R 10.18653/v1/2025.findings-acl.674
%U https://aclanthology.org/2025.findings-acl.674/
%U https://doi.org/10.18653/v1/2025.findings-acl.674
%P 12981-12993
Markdown (Informal)
[Improving Causal Interventions in Amnesic Probing with Mean Projection or LEACE](https://aclanthology.org/2025.findings-acl.674/) (Dobrzeniecka et al., Findings 2025)
ACL