Few-shot Relation Extraction
Few-Shot Relation Extraction is a relation extraction paradigm that addresses the identification of semantic relations between entities in text using a minimal number of labeled instances per relation, typically leveraging meta-learning or transfer learning to generalize from limited supervision.
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2017–2026
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Large language models are few-shot clinical information extractors
Monica Agrawal, Stefan Hegselmann, Hunter Lang et al. · 2022 · 297 citations · Full text
FewRel 2.0: Towards More Challenging Few-Shot Relation Classification
Tianyu Gao, Xu Han, Hao Zhu et al. · 2019 · 247 citations · Full text
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Tsinghua University
Beijing, China
6 h-index
23 publications
2.1K citations

Chinese Academy of Sciences
Beijing, China
4 h-index
9 publications
218 citations

Harbin Institute of Technology
Harbin, China
4 h-index
4 publications
150 citations

Zhejiang University
Hangzhou, China
3 h-index
16 publications
2.7K citations
University of Chinese Academy of Sciences
Beijing, China
3 h-index
9 publications
214 citations
Chinese University of Hong Kong, Shenzhen
Shenzhen, China
3 h-index
7 publications
196 citations

Beijing University of Posts and Telecommunications
Beijing, China
3 h-index
6 publications
232 citations
Singapore University of Technology and Design
Singapore, Singapore
3 h-index
4 publications
129 citations
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Repository · 7 publications · 239 citations
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