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Found 4 papers, 1 papers with code
Labels in Extremes: How Well Calibrated are Extreme Multi-label Classifiers?
To judge whether an extreme classifier is indeed suited to this task, one can look, for example, to whether it returns \emph{calibrated} probabilities, which has hitherto not been done in this field.
Zero-Shot Learning Over Large Output Spaces : Utilizing Indirect Knowledge Extraction from Large Language Models
Extreme Multi-label Learning (XMC) is a task that allocates the most relevant labels for an instance from a predefined label set.
UER: An Open-Source Toolkit for Pre-training Models
Existing works, including ELMO and BERT, have revealed the importance of pre-training for NLP tasks.
Multi-task Learning for Chinese Word Usage Errors Detection
Chinese word usage errors often occur in non-native Chinese learners' writing.
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