Debiasing NER.pdf

2023.acl-short.98.pdf
Preview of Debiasing NER
🔗 Source: aclanthology.org
📊 Size: 395 KB
📄 Pages: 12 pages
⬇️ Downloads: 25

Summary

Researchers propose a reranking-based approach, RerankNER, to debias generative Named Entity Recognition (NER) by calibrating sequence likelihood using a contrastive loss, which makes estimated sequence likelihoods consistent with their relative task performance, and achieve competitive results on 8 widely-used datasets.

Description

Researchers propose a reranking-based approach, RerankNER, to debias generative Named Entity Recognition (NER) by calibrating sequence likelihood using a...

Technical Information

  • File Format: PDF
  • File Size: 395 KB
  • Pages: 12
  • Language: EN
  • Total Downloads: 25
  • Last Updated: 1 month ago

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