natural-language-processing-7

Continual Named Entity Recognition

3260 papers • 126 benchmarks • 313 datasets

Continual learning for named entity recogntion

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FG-1-PG-1

Most implemented papers

Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition

Junhao Zheng, Zhanxian Liang, Haibin Chen, Qianli Ma•Fri Oct 07 2022

This work proposes a unified causal framework to retrieve the causality from both new entity types and Other-Class and applies curriculum learning to mitigate the impact of label noise and introduce a self-adaptive weight for balancing the causal effects between new entities types and other-Class.

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Continual Named Entity Recognition without Catastrophic Forgetting

Duzhen Zhang, Wei Cong, Jiahua Dong, Yahan Yu, Xiuyi Chen, Yonggang Zhang, Zhen Fang•Sun Oct 22 2023

This paper introduces a pooled feature distillation loss that skillfully navigates the trade-off between retaining knowledge of old entity types and acquiring new ones, thereby more effectively mitigating the problem of catastrophic forgetting.

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A Neural Span-Based Continual Named Entity Recognition Model

Qingcai Chen, Yunan Zhang•Wed Feb 22 2023

Experiments on synthetic CL datasets derived from OntoNotes and Few-NERD show that SpanKL significantly outperforms previous SoTA in many aspects, and obtains the smallest gap from CL to the upper bound revealing its high practiced value.

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