mlsanityData to 14 Oct 2026

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

arXiv 2412.15785 ↗First posted 20 Dec 2024cs.CLcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 16 of its 51 references that are in the map. First posted on arXiv 20 Dec 2024.

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16 of 51 references.

References · 16

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4 more
  1. 2021Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learningcited by 34
  2. 2021How is BERT surprised? Layerwise detection of linguistic anomaliescited by 24
  3. 2023CLIMB: Curriculum Learning for Infant-inspired Model Buildingcited by 20
  4. 2024Natural Language Processing RELIES on Linguisticscited by 9

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