Few-shot Name Entity Recognition on StackOverflow

Xinwei Chen, Kun Li, Tianyou Song, Jiangjian Guo
4/15/2024
cs.CLcs.AI

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Abstract

StackOverflow, with its vast question repository and limited labeled examples, raise an annotation challenge for us. We address this gap by proposing RoBERTa+MAML, a few-shot named entity recognition (NER) method leveraging meta-learning. Our approach, evaluated on the StackOverflow NER corpus (27 entity types), achieves a 5% F1 score improvement over the baseline. We improved the results further domain-specific phrase processing enhance results.

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Cite this paper

@article{chen2024fewshot,
  title  = {Few-shot Name Entity Recognition on StackOverflow},
  author = {Xinwei Chen and Kun Li and Tianyou Song and Jiangjian Guo},
  year   = {2024},
  eprint = {2404.09405},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.09405v2}
}

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