arXiv:2008.10570
Example-Based Named Entity Recognition
원문 초록
We present a novel approach to named entity recognition (NER) in the presence of scarce data that we call example-based NER. Our train-free few-shot learning approach takes inspiration from question-answering to identify entity spans in a new and unseen domain. In comparison with the current state-of-the-art, the proposed method performs significantly better, especially when using a low number of support examples.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Selecting and Merging: Towards Adaptable and Scalable Named Entity Recognition with Large Language Models
Label-Guided In-Context Learning for Named Entity Recognition
Named Entity Recognition in Historical Italian: The Case of Giacomo Leopardi's Zibaldone
Flippi: End To End GenAI Assistant for E-Commerce
Better Semi-supervised Learning for Multi-domain ASR Through Incremental Retraining and Data Filtering
Efficient Data Selection for Domain Adaptation of ASR Using Pseudo-Labels and Multi-Stage Filtering
토론
이 논문과 연결된 포럼 글이 아직 없습니다.