mlsanityData to 7 Oct 2026

Towards better substitution-based word sense induction

arXiv 1905.12598 ↗First posted 29 May 2019cs.CLcited by 18

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Abstract (arXiv)

Word sense induction (WSI) is the task of unsupervised clustering of word usages within a sentence to distinguish senses. Recent work obtain strong results by clustering lexical substitutes derived from pre-trained RNN language models (ELMo). Adapting the method to BERT improves the scores even further. We extend the previous method to support a dynamic rather than a fixed number of clusters as supported by other prominent methods, and propose a method for interpreting the resulting clusters by associating them with their most informative substitutes. We then perform extensive error analysis revealing the remaining sources of errors in the WSI task. Our code is available at https://github.com/asafamr/bertwsi.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 May 2019.

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Citing papers per year: 2021: 6; 2022: 6; 2023: 0; 2024: 4; 2025: 1; 2026: 1.

18 papers.

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  1. 2021Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Surveycited by 457
  2. 2024Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Researchcited by 26
  3. 2021Characterizing English Variation across Social Media Communities with BERTcited by 20
  4. 2022Always Keep your Target in Mind: Studying Semantics and Improving Performance of Neural Lexical Substitutioncited by 12
  5. 2021Large Scale Substitution-based Word Sense Inductioncited by 9
  6. 2022RuDSI: graph-based word sense induction dataset for Russiancited by 7
  7. 2021PolyLM: Learning about Polysemy through Language Modelingcited by 5
  8. 2022Towards Automatic Construction of Filipino WordNet: Word Sense Induction and Synset Induction Using Sentence Embeddingscited by 3
  9. 2022Tracing Semantic Variation in Slangcited by 3
  10. 2024To Word Senses and Beyond: Inducing Concepts with Contextualized Language Modelscited by 3
  11. 2021Deriving Word Vectors from Contextualized Language Models using Topic-Aware Mention Selectioncited by 2
  12. 2022BOS at LSCDiscovery: Lexical Substitution for Interpretable Lexical Semantic Change Detectioncited by 2
6 more
  1. 2025Large Language Models for History, Philosophy, and Sociology of Science: Interpretive Uses, Methodological Challenges, and Critical Perspectivescited by 2
  2. 2026In the LLM era, Word Sense Induction remains unsolvedcited by 2
  3. 2024Multilingual Substitution-based Word Sense Inductioncited by 1
  4. 2021Text analysis and deep learning: A network approachcited by 0
  5. 2022Word Sense Induction with Hierarchical Clustering and Mutual Information Maximizationcited by 0
  6. 2024Deep-change at AXOLOTL-24: Orchestrating WSD and WSI Models for Semantic Change Modelingcited by 0