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Main Authors: Lasri, Karim, Pimentel, Tiago, Lenci, Alessandro, Poibeau, Thierry, Cotterell, Ryan
Format: Preprint
Published: 2022
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Online Access:https://arxiv.org/abs/2204.08831
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author Lasri, Karim
Pimentel, Tiago
Lenci, Alessandro
Poibeau, Thierry
Cotterell, Ryan
author_facet Lasri, Karim
Pimentel, Tiago
Lenci, Alessandro
Poibeau, Thierry
Cotterell, Ryan
contents A central quest of probing is to uncover how pre-trained models encode a linguistic property within their representations. An encoding, however, might be spurious-i.e., the model might not rely on it when making predictions. In this paper, we try to find encodings that the model actually uses, introducing a usage-based probing setup. We first choose a behavioral task which cannot be solved without using the linguistic property. Then, we attempt to remove the property by intervening on the model's representations. We contend that, if an encoding is used by the model, its removal should harm the performance on the chosen behavioral task. As a case study, we focus on how BERT encodes grammatical number, and on how it uses this encoding to solve the number agreement task. Experimentally, we find that BERT relies on a linear encoding of grammatical number to produce the correct behavioral output. We also find that BERT uses a separate encoding of grammatical number for nouns and verbs. Finally, we identify in which layers information about grammatical number is transferred from a noun to its head verb.
format Preprint
id arxiv_https___arxiv_org_abs_2204_08831
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Probing for the Usage of Grammatical Number
Lasri, Karim
Pimentel, Tiago
Lenci, Alessandro
Poibeau, Thierry
Cotterell, Ryan
Computation and Language
A central quest of probing is to uncover how pre-trained models encode a linguistic property within their representations. An encoding, however, might be spurious-i.e., the model might not rely on it when making predictions. In this paper, we try to find encodings that the model actually uses, introducing a usage-based probing setup. We first choose a behavioral task which cannot be solved without using the linguistic property. Then, we attempt to remove the property by intervening on the model's representations. We contend that, if an encoding is used by the model, its removal should harm the performance on the chosen behavioral task. As a case study, we focus on how BERT encodes grammatical number, and on how it uses this encoding to solve the number agreement task. Experimentally, we find that BERT relies on a linear encoding of grammatical number to produce the correct behavioral output. We also find that BERT uses a separate encoding of grammatical number for nouns and verbs. Finally, we identify in which layers information about grammatical number is transferred from a noun to its head verb.
title Probing for the Usage of Grammatical Number
topic Computation and Language
url https://arxiv.org/abs/2204.08831