Papers with Span Boosting Module

1 papers
A Streamlined Span-based Factorization Method for Few Shot Named Entity Recognition (2024.lrec-main)

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Challenge: Existing approaches to few-shot named entity recognition require large amounts of labeled data.
Approach: They propose a streamlined span-based factorization method that solves few-shot NER problem . they propose to decompose the span-level alignment problem into several refined procedures .
Outcome: The proposed method achieves an average F1 score improvement of 12 points on the FewNERD dataset and 10 points on SNIPS dataset.

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