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German in Flux: Detecting Metaphoric Change via Word Entropy.

, , , , and . CoNLL, page 354-367. Association for Computational Linguistics, (2017)

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Simulating Lexical Semantic Change from Sense-Annotated Data., and . CoRR, (2020)CL-IMS @ DIACR-Ita: Volente o Nolente: BERT does not outperform SGNS on Semantic Change Detection., , , , and . CoRR, (2020)The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change., , , , , , , , and . CoRR, (2023)IMS at SemEval-2020 Task 1: How Low Can You Go? Dimensionality in Lexical Semantic Change Detection., , , and . SemEval@COLING, page 81-89. International Committee for Computational Linguistics, (2020)The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change., , , , , , , , and . EACL (Demonstrations), page 137-149. Association for Computational Linguistics, (2024)Hypernyms under Siege: Linguistically-motivated Artillery for Hypernymy Detection., , and . EACL (1), page 65-75. Association for Computational Linguistics, (2017)Effects of Pre- and Post-Processing on type-based Embeddings in Lexical Semantic Change Detection., , , and . EACL, page 125-137. Association for Computational Linguistics, (2021)CCOHA: Clean Corpus of Historical American English., , , and . LREC, page 6958-6966. European Language Resources Association, (2020)SURel: A Gold Standard for Incorporating Meaning Shifts into Term Extraction., , and . *SEM@NAACL-HLT, page 1-8. Association for Computational Linguistics, (2019)A Wind of Change: Detecting and Evaluating Lexical Semantic Change across Times and Domains., , , and . ACL (1), page 732-746. Association for Computational Linguistics, (2019)