Low-Resource Named Entity Recognition: Can One-vs-All AUC Maximization Help?

no code implementations • 2 Nov 2023 • Ngoc Dang Nguyen, Wei Tan, Lan Du, Wray Buntine, Richard Beare, Changyou Chen

Named entity recognition (NER), a task that identifies and categorizes named entities such as persons or organizations from text, is traditionally framed as a multi-class classification problem.

Low Resource Named Entity Recognition Meta-Learning +4

Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets

no code implementations • 15 Apr 2023 • Jionghao Lin, Wei Tan, Ngoc Dang Nguyen, David Lang, Lan Du, Wray Buntine, Richard Beare, Guanliang Chen, Dragan Gasevic

We note that many prior studies on classifying educational DAs employ cross entropy (CE) loss to optimize DA classifiers on low-resource data with imbalanced DA distribution.

AUC Maximization for Low-Resource Named Entity Recognition

no code implementations • 9 Dec 2022 • Ngoc Dang Nguyen, Wei Tan, Wray Buntine, Richard Beare, Changyou Chen, Lan Du

To the best of our knowledge, this is the first work that brings AUC maximization to the NER setting.

Low Resource Named Entity Recognition named-entity-recognition +2

Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios

no code implementations • 11 Nov 2022 • Ngoc Dang Nguyen, Lan Du, Wray Buntine, Changyou Chen, Richard Beare

Domain adaptation is an effective solution to data scarcity in low-resource scenarios.

Domain Adaptation