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Contextualized language models for semantic change detection: lessons
  learned

Contextualized language models for semantic change detection: lessons learned

31 August 2022
Andrey Kutuzov
Erik Velldal
Lilja Øvrelid
ArXivPDFHTML

Papers citing "Contextualized language models for semantic change detection: lessons learned"

4 / 4 papers shown
Title
Norm of Mean Contextualized Embeddings Determines their Variance
Norm of Mean Contextualized Embeddings Determines their Variance
Hiroaki Yamagiwa
Hidetoshi Shimodaira
29
0
0
17 Sep 2024
A Tale of Two Laws of Semantic Change: Predicting Synonym Changes with
  Distributional Semantic Models
A Tale of Two Laws of Semantic Change: Predicting Synonym Changes with Distributional Semantic Models
Bastien Liétard
Mikaela Keller
Pascal Denis
35
1
0
30 May 2023
Unsupervised Semantic Variation Prediction using the Distribution of
  Sibling Embeddings
Unsupervised Semantic Variation Prediction using the Distribution of Sibling Embeddings
Taichi Aida
Danushka Bollegala
28
8
0
15 May 2023
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection
Dominik Schlechtweg
Barbara McGillivray
Simon Hengchen
Haim Dubossarsky
Nina Tahmasebi
165
236
0
22 Jul 2020
1