Papers with calibration and

1 papers
Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation? (2024.emnlp-main)

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Challenge: Named Entity Recognition (NER) is a key task in NLP to find mentions of named entities and classify them into predefined categories.
Approach: They investigated the impact of data augmentation on confidence calibration and uncertainty estimation in Named Entity Recognition (NER) tasks.
Outcome: The data augmentation improves calibration and uncertainty in cross-genre and cross-lingual setting, especially in-domain setting.

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