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Explaining and Improving BERT Performance on Lexical Semantic Change Detection ...
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DiscoWUG: Discovered Diachronic Word Usage Graphs for German ...
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Challenges for computational lexical semantic change ...
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Abstract:
The computational study of lexical semantic change (LSC) has taken off in the past few years and we are seeing increasing interest in the field, from both computational sciences and linguistics. Most of the research so far has focused on methods for modelling and detecting semantic change using large diachronic textual data, with the majority of the approaches employing neural embeddings. While methods that offer easy modelling of diachronic text are one of the main reasons for the spiking interest in LSC, neural models leave many aspects of the problem unsolved. The field has several open and complex challenges. In this chapter, we aim to describe the most important of these challenges and outline future directions. ...
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URL: https://zenodo.org/record/5040321 https://dx.doi.org/10.5281/zenodo.5040321
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DiscoWUG: Discovered Diachronic Word Usage Graphs for German ...
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DiscoWUG: Discovered Diachronic Word Usage Graphs for German ...
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CL-IMS @ DIACR-Ita: Volente o Nolente: BERT does not outperform SGNS on Semantic Change Detection ...
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IMS at SemEval-2020 Task 1: How low can you go? Dimensionality in Lexical Semantic Change Detection ...
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SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection ...
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OP-IMS @ DIACR-Ita: Back to the Roots: SGNS+OP+CD still rocks Semantic Change Detection ...
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