Papers with discriminator model

1 papers
Self-Cleaning: Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instances (2024.findings-naacl)

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Challenge: Existing methods to train named entity recognition models on noisy data are expensive and time-intensive to accumulate.
Approach: They propose to denoise noisy NER data with guidance from a small set of clean instances.
Outcome: The proposed method can improve on large-scale datasets with a small guidance set.

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