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        <title>ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics</title>
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    <abstract>The majority of contemporary computational methods for lexical semantic change (LSC) detection are based on neural embedding distributional representations. Although these models perform well on LSC benchmarks, their results are often difficult to interpret. We explore an alternative approach that relies solely on frame semantics. We show that this method is effective for detecting semantic change and can even outperform many distributional semantic models. Finally, we present a detailed quantitative and qualitative analysis of its predictions, demonstrating that they are both plausible and highly interpretable.</abstract>
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%0 Conference Proceedings
%T ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics
%A Tat, Bach Phan
%A Heylen, Kris
%A De Pascale, Stefano
%A Geeraerts, Dirk
%A Speelman, Dirk
%Y Mohammad, Saif M.
%Y Ousidhoum, Nedjma
%S Proceedings of the 15th Joint Conference on Lexical and Computational Semantics (*SEM 2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-413-2
%F tat-etal-2026-reframe
%X The majority of contemporary computational methods for lexical semantic change (LSC) detection are based on neural embedding distributional representations. Although these models perform well on LSC benchmarks, their results are often difficult to interpret. We explore an alternative approach that relies solely on frame semantics. We show that this method is effective for detecting semantic change and can even outperform many distributional semantic models. Finally, we present a detailed quantitative and qualitative analysis of its predictions, demonstrating that they are both plausible and highly interpretable.
%U https://aclanthology.org/2026.starsem-conference.5/
%P 83-97

Markdown (Informal)

[ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics](https://aclanthology.org/2026.starsem-conference.5/) (Tat et al., *SEM 2026)

• ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics (Tat et al., *SEM 2026)

ACL

• Bach Phan Tat, Kris Heylen, Stefano De Pascale, Dirk Geeraerts, and Dirk Speelman. 2026. ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics. In Proceedings of the 15th Joint Conference on Lexical and Computational Semantics (*SEM 2026), pages 83–97, San Diego, California, United States. Association for Computational Linguistics.