Papers by Carel van Niekerk
A Confidence-based Acquisition Model for Self-supervised Active Learning and Label Correction (2025.tacl-1)
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Carel van Niekerk, Christian Geishauser, Michael Heck, Shutong Feng, Hsien-chin Lin, Nurul Lubis, Benjamin Ruppik, Renato Vukovic, Milica Gašić
| Challenge: | Existing approaches to training deep neural networks require large amounts of meticulously annotated data. |
| Approach: | They propose a pool-based active learning framework that requires expert annotators to label only a fraction of a sequence and facilitates self-supervision for the remainder of the sequence. |
| Outcome: | The proposed model outperforms baselines on dialogue belief tracking tasks. |