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pro vyhledávání: '"Kurtyigit, Sinan"'
While there is a large amount of research in the field of Lexical Semantic Change Detection, only few approaches go beyond a standard benchmark evaluation of existing models. In this paper, we propose a shift of focus from change detection to change
Externí odkaz:
http://arxiv.org/abs/2106.03111
Autor:
Laicher, Severin, Kurtyigit, Sinan, Schlechtweg, Dominik, Kuhn, Jonas, Walde, Sabine Schulte im
Type- and token-based embedding architectures are still competing in lexical semantic change detection. The recent success of type-based models in SemEval-2020 Task 1 has raised the question why the success of token-based models on a variety of other
Externí odkaz:
http://arxiv.org/abs/2103.07259
Lexical semantic change detection is a new and innovative research field. The optimal fine-tuning of models including pre- and post-processing is largely unclear. We optimize existing models by (i) pre-training on large corpora and refining on diachr
Externí odkaz:
http://arxiv.org/abs/2101.09368