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We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e. g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i. e., to model polysemy).
#3 best model for Sentiment Analysis on SST-5 Fine-grained classification
Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive.
SOTA for Named Entity Recognition on NCBI-disease (using extra training data)
Identifying the intent of a citation in scientific papers (e. g., background information, use of methods, comparing results) is critical for machine reading of individual publications and automated analysis of the scientific literature.