Universality, diversity and idiosyncrasy
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wg3:wg3_meeting_2025-05-06_edit [2025/06/23 16:07] – gulsen.eryigitwg3:wg3_meeting_2025-05-06_edit [2025/07/11 11:38] (current) – gulsen.eryigit
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 ======Minutes from the eleventh WG 14 meeting (online 2025-05-06 12:00 CET)====== ======Minutes from the eleventh WG 14 meeting (online 2025-05-06 12:00 CET)======
-===== Agenda =====+==== Agenda ====
  
  
-  * Invited talk by Juri Alexander Opitz on "Natural Language Processing RELIES on Linguistics" by Opitz. et al. 2025 +  * Invited talk by Juri Alexander Opitz on "[[https://direct.mit.edu/coli/article/doi/10.1162/coli_a_00560/128736|Natural Language Processing RELIES on Linguistics]]" by Opitz. et al. 2025 
   * Discussion on the use of LLMs within Unidive   * Discussion on the use of LLMs within Unidive
   * Task 3.5: Evaluation campaign AdMIRe Advancing Multimodal Idiomaticity Representation call for language leaders and annotators by Aline Villavicencio    * Task 3.5: Evaluation campaign AdMIRe Advancing Multimodal Idiomaticity Representation call for language leaders and annotators by Aline Villavicencio 
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 Large Language Models (LLMs) have become capable of generating highly fluent text in certain languages, without modules specially designed to capture grammar or semantic coherence. What does this mean for the future of linguistic expertise in NLP? We highlight several aspects in which NLP (still) relies on linguistics, or where linguistic thinking can illuminate new directions. We argue our case around the acronym RELIES, which encapsulates six major facets where linguistics contributes to NLP: Resources, Evaluation, Low-resource settings, Interpretability, Explanation, and the Study of language. This list is not exhaustive, nor is linguistics the main point of reference for every effort under these themes; but at a macro level, these facets highlight the enduring importance of studying machine systems vis-a-vis systems of human language. Large Language Models (LLMs) have become capable of generating highly fluent text in certain languages, without modules specially designed to capture grammar or semantic coherence. What does this mean for the future of linguistic expertise in NLP? We highlight several aspects in which NLP (still) relies on linguistics, or where linguistic thinking can illuminate new directions. We argue our case around the acronym RELIES, which encapsulates six major facets where linguistics contributes to NLP: Resources, Evaluation, Low-resource settings, Interpretability, Explanation, and the Study of language. This list is not exhaustive, nor is linguistics the main point of reference for every effort under these themes; but at a macro level, these facets highlight the enduring importance of studying machine systems vis-a-vis systems of human language.
 +
 +Presentation available "[[https://docs.google.com/presentation/d/1Vs05R8zEXpzaA2DLGOeL2qM1CKRe1dRNdyhiSRvA5DE/edit?slide=id.p#slide=id.p]]"
  
 ==== List of Participants ==== ==== List of Participants ====
wg3/wg3_meeting_2025-05-06_edit.1750687678.txt.gz · Last modified: by gulsen.eryigit