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Representation Problems in Linguistic Annotations: Ambiguity, Variation, Uncertainty, Error and Bias
The development of linguistic corpora is fraught with various problems of annotation and representation.
Negation, Coordination, and Quantifiers in Contextualized Language Models
With the success of contextualized language models, much research explores what these models really learn and in which cases they still fail.
Explaining Contextualization in Language Models using Visual Analytics
Despite the success of contextualized language models on various NLP tasks, it is still unclear what these models really learn.
DiaSense at SemEval-2020 Task 1: Modeling Sense Change via Pre-trained BERT Embeddings
This paper describes DiaSense, a system developed for Task 1 {`}Unsupervised Lexical Semantic Change Detection{'} of SemEval 2020.
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