mlsanityData to 7 Oct 2026

Multilingual Substitution-based Word Sense Induction

arXiv 2405.11086 ↗First posted 17 May 2024cs.CLcited by 1

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Abstract (arXiv)

Word Sense Induction (WSI) is the task of discovering senses of an ambiguous word by grouping usages of this word into clusters corresponding to these senses. Many approaches were proposed to solve WSI in English and a few other languages, but these approaches are not easily adaptable to new languages. We present multilingual substitution-based WSI methods that support any of 100 languages covered by the underlying multilingual language model with minimal to no adaptation required. Despite the multilingual capabilities, our methods perform on par with the existing monolingual approaches on popular English WSI datasets. At the same time, they will be most useful for lower-resourced languages which miss lexical resources available for English, thus, have higher demand for unsupervised methods like WSI.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 16 of its 38 references that are in the map. First posted on arXiv 17 May 2024.

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16 of 38 references.

References · 16

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  10. 2018Word Sense Induction with Neural biLM and Symmetric Patternscited by 18
  11. 2019Towards better substitution-based word sense inductioncited by 18
  12. 2022Always Keep your Target in Mind: Studying Semantics and Improving Performance of Neural Lexical Substitutioncited by 12
4 more
  1. 2021Large Scale Substitution-based Word Sense Inductioncited by 9
  2. 2018AutoSense Model for Word Sense Inductioncited by 7
  3. 2021PolyLM: Learning about Polysemy through Language Modelingcited by 5
  4. 2018RUSSE'2018: A Shared Task on Word Sense Induction for the Russian Languagecited by 4

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