Papers with SCoNE

1 papers
SCoNE: a Self-Correcting and Noise-Augmented Method for Complex Biological and Chemical Named Entity Recognition (2026.eacl-long)

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Challenge: Named Entity Recognition (NER) is a fundamental task aimed at identifying entities such as names, locations, and organizations.
Approach: They propose a self-correcting and noise-augmented method for complex Biological and Chemical Named Entity Recognition that improves learning diversity and confidence.
Outcome: The proposed method outperforms baseline methods on CHEMDNER and microbial ecology datasets by 1.80 and 2.73 F1-scores.

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