An Enhanced Span-based Decomposition Method for Few-Shot Sequence Labeling

Understand

Few-Shot Sequence Labeling (FSSL) is a canonical paradigm for the tagging models, e.g., named entity recognition and slot filling, to generalize on an emerging, resource-scarce domain.

• Recently, the metric-based meta-learning framework has been recognized as a promising approach for FSSL.
• However, most prior works assign a label to each token based on the token-level similarities, which ignores the integrality of named entities or slots.
• To this end, in this paper, we propose ESD, an Enhanced Span-based Decomposition method for FSSL.