Towards Robust Named Entity Recognition via Temporal Domain Adaptation and Entity Context Understanding
Keywords:Natural Language Processing, Named Entity Recognition, Robustness, Generalization, Temporal Drift
AbstractNamed Entity Recognition models perform well on benchmark datasets but fail to generalize well even in the same domain. The goal of my th esis is to quantify the degree of in-domain generalization in NER, probe models for entity name vs. context learning and finally improve their robustness, focusing on the recognition of ethnically diverse entities and new entities over time when the models are deployed.
How to Cite
Agarwal, O. (2022). Towards Robust Named Entity Recognition via Temporal Domain Adaptation and Entity Context Understanding. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12866-12867. https://doi.org/10.1609/aaai.v36i11.21570
The Twenty - Seventh AAAI / SIGAI Doctoral Consortium