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Dice Loss for Data-imbalanced NLP Tasks
Many NLP tasks such as tagging and machine reading comprehension are faced with the severe data imbalance issue: negative examples significantly outnumber positive examples, and the huge number of background examples (or easy-negative examples) overwhelms the training.
Ranked #1 on
Chinese Named Entity Recognition
on OntoNotes 4
(using extra training data)
Chinese Named Entity Recognition
Machine Reading Comprehension
+5
