This position paper investigates the potential of integrating insights from language impairment research and its clinical treatment to develop human-inspired learning strategies and evaluation frameworks for language models (LMs). We inspect the theoretical underpinnings underlying some influential linguistically motivated training approaches derived from neurolinguistics and, particularly, aphasiology, aimed at enhancing the recovery and generalization of linguistic skills in aphasia treatment, with a primary focus on those targeting the syntactic domain. We highlight how these insights can inform the design of rigorous assessments for LMs, specifically in their handling of complex syntactic phenomena, as well as their implications for developing human-like learning strategies, aligning with efforts to create more sustainable and cognitively plausible natural language processing (NLP) models.

Learning from Impairment: Leveraging Insights from Clinical Linguistics in Language Modelling Research

Dominique Brunato
2025

Abstract

This position paper investigates the potential of integrating insights from language impairment research and its clinical treatment to develop human-inspired learning strategies and evaluation frameworks for language models (LMs). We inspect the theoretical underpinnings underlying some influential linguistically motivated training approaches derived from neurolinguistics and, particularly, aphasiology, aimed at enhancing the recovery and generalization of linguistic skills in aphasia treatment, with a primary focus on those targeting the syntactic domain. We highlight how these insights can inform the design of rigorous assessments for LMs, specifically in their handling of complex syntactic phenomena, as well as their implications for developing human-like learning strategies, aligning with efforts to create more sustainable and cognitively plausible natural language processing (NLP) models.
Campo DC Valore Lingua
dc.authority.orgunit Istituto di linguistica computazionale "Antonio Zampolli" - ILC en
dc.authority.people Dominique Brunato en
dc.collection.id.s 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d *
dc.collection.name 04.01 Contributo in Atti di convegno *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 918 *
dc.date.accessioned 2025/01/28 14:45:09 -
dc.date.available 2025/01/28 14:45:09 -
dc.date.firstsubmission 2025/01/28 12:05:11 *
dc.date.issued 2025 -
dc.date.submission 2025/01/28 12:05:11 *
dc.description.abstracteng This position paper investigates the potential of integrating insights from language impairment research and its clinical treatment to develop human-inspired learning strategies and evaluation frameworks for language models (LMs). We inspect the theoretical underpinnings underlying some influential linguistically motivated training approaches derived from neurolinguistics and, particularly, aphasiology, aimed at enhancing the recovery and generalization of linguistic skills in aphasia treatment, with a primary focus on those targeting the syntactic domain. We highlight how these insights can inform the design of rigorous assessments for LMs, specifically in their handling of complex syntactic phenomena, as well as their implications for developing human-like learning strategies, aligning with efforts to create more sustainable and cognitively plausible natural language processing (NLP) models. -
dc.description.allpeople Brunato, Dominique -
dc.description.allpeopleoriginal Dominique Brunato en
dc.description.fulltext open en
dc.description.numberofauthors 1 -
dc.identifier.isbn 979-8-89176-196-4 en
dc.identifier.source manual *
dc.identifier.uri https://hdl.handle.net/20.500.14243/532162 -
dc.identifier.url https://aclanthology.org/2025.coling-main.281/ en
dc.language.iso eng en
dc.relation.conferencedate January 19–24, 2025 en
dc.relation.conferencename 31st International Conference on Computational Linguistics en
dc.relation.conferenceplace Abu Dhabi, UAE en
dc.relation.firstpage 4167 en
dc.relation.ispartofbook Proceedings of the 31st International Conference on Computational Linguistics en
dc.relation.lastpage 4174 en
dc.relation.numberofpages 8 en
dc.subject.keywordseng language modelling, clinical linguistics, syntactic complexity -
dc.subject.singlekeyword language modelling *
dc.subject.singlekeyword clinical linguistics *
dc.subject.singlekeyword syntactic complexity *
dc.title Learning from Impairment: Leveraging Insights from Clinical Linguistics in Language Modelling Research en
dc.type.circulation Internazionale en
dc.type.driver info:eu-repo/semantics/conferenceObject -
dc.type.full 04 Contributo in convegno::04.01 Contributo in Atti di convegno it
dc.type.impactfactor si en
dc.type.miur 273 -
iris.mediafilter.data 2025/04/12 03:27:10 *
iris.orcid.lastModifiedDate 2025/01/28 14:45:09 *
iris.orcid.lastModifiedMillisecond 1738071909303 *
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