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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Few-Shot Named Entity Recognition: An Empirical Baseline Study
Jiaxin Huang, Chunyuan Li, Krishan Subudhi, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
Open Access | Times Cited: 83

Showing 1-25 of 83 citing articles:

Unified Structure Generation for Universal Information Extraction
Yaojie Lu, Q. Liu, Dai Dai, et al.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022)
Open Access | Times Cited: 261
Template-free Prompt Tuning for Few-shot NER
Ruotian Ma, Xin Zhou, Tao Gui, et al.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2022)
Open Access | Times Cited: 81
Named Entity Recognition and Classification in Historical Documents: A Survey
Maud Ehrmann, Ahmed Hamdi, Elvys Linhares Pontes, et al.
ACM Computing Surveys (2023) Vol. 56, Iss. 2, pp. 1-47
Open Access | Times Cited: 49
Large language models for generative information extraction: a survey
Derong Xu, Wei Chen, Wenjun Peng, et al.
Frontiers of Computer Science (2024) Vol. 18, Iss. 6
Open Access | Times Cited: 39
State-of-the-art generalisation research in NLP: A taxonomy and review
Dieuwke Hupkes, Mario Giulianelli, Verna Dankers, et al.
arXiv (Cornell University) (2022)
Open Access | Times Cited: 39
Universal Information Extraction as Unified Semantic Matching
Jie Lou, Yaojie Lu, Dai Dai, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 11, pp. 13318-13326
Open Access | Times Cited: 26
Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training
Meng Yu, Yunyi Zhang, Jiaxin Huang, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
Open Access | Times Cited: 44
PromptNER: Prompt Locating and Typing for Named Entity Recognition
Yongliang Shen, Zeqi Tan, Shuhui Wu, et al.
(2023)
Open Access | Times Cited: 18
Improving Feature Extraction Using a Hybrid of CNN and LSTM for Entity Identification
Elham Parsaeimehr, Mehdi Fartash, Javad Akbari Torkestani
Neural Processing Letters (2023) Vol. 55, Iss. 5, pp. 5979-5994
Closed Access | Times Cited: 16
SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognition
Jianing Wang, Chengyu Wang, Chuanqi Tan, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 22
Few-shot Named Entity Recognition: Definition, Taxonomy and Research Directions
Vincenzo Moscato, Marco Postiglione, Giancarlo Sperlí
ACM Transactions on Intelligent Systems and Technology (2023) Vol. 14, Iss. 5, pp. 1-46
Open Access | Times Cited: 11
Learning In-context Learning for Named Entity Recognition
Jiawei Chen, Yaojie Lu, Hongyu Lin, et al.
(2023), pp. 13661-13675
Open Access | Times Cited: 10
SQGE: Support-query prototype guidance and enhancement for few-shot relational triple extraction
Gao Chen, Xuan Zhang, Zhi Jin, et al.
Neural Networks (2025) Vol. 185, pp. 107172-107172
Closed Access
Simplify Prompt Template and Optimum Label-Select for Few-Shot NER
Qin Xiao, Shuo Tan, Xin Chun, et al.
Communications in computer and information science (2025), pp. 370-381
Closed Access
Advancements in few-shot nested Named Entity Recognition: The efficacy of meta-learning convolutional approaches
S.C. Zhu, Yuan Yang, Lin Shi, et al.
Neurocomputing (2025), pp. 129893-129893
Closed Access
Few-shot biomedical NER empowered by LLMs-assisted data augmentation and multi-scale feature extraction
Di Zhao, Wenxuan Mu, Xiangxing Jia, et al.
BioData Mining (2025) Vol. 18, Iss. 1
Open Access
ClinicalRadioBERT: Knowledge-Infused Few Shot Learning for Clinical Notes Named Entity Recognition
Saed Rezayi, Haixing Dai, Zhengliang Liu, et al.
Lecture notes in computer science (2022), pp. 269-278
Closed Access | Times Cited: 15
Decomposed Meta-Learning for Few-Shot Sequence Labeling
Tingting Ma, Qianhui Wu, Huiqiang Jiang, et al.
IEEE/ACM Transactions on Audio Speech and Language Processing (2024) Vol. 32, pp. 1980-1993
Closed Access | Times Cited: 3
TKDP: Threefold Knowledge-Enriched Deep Prompt Tuning for Few-Shot Named Entity Recognition
Jiang Liu, Hao Fei, Fei Li, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 11, pp. 6397-6409
Closed Access | Times Cited: 3
A few-shot word-structure embedded model for bridge inspection reports learning
Yuchen Wang, Yanjie Zhu, Wen Xiong, et al.
Advanced Engineering Informatics (2024) Vol. 62, pp. 102664-102664
Closed Access | Times Cited: 3
Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation
Jiaxin Huang, Meng Yu, Jiawei Han
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022), pp. 605-614
Open Access | Times Cited: 14
Semi-supervised geological disasters named entity recognition using few labeled data
Xinya Lei, Weijing Song, Runyu Fan, et al.
GeoInformatica (2022) Vol. 27, Iss. 2, pp. 263-288
Closed Access | Times Cited: 13
Decomposed Two-Stage Prompt Learning for Few-Shot Named Entity Recognition
Feiyang Ye, Liang Huang, Senjie Liang, et al.
Information (2023) Vol. 14, Iss. 5, pp. 262-262
Open Access | Times Cited: 7
Infectious risk events and their novelty in event-based surveillance: new definitions and annotated corpus
François Delon, Gabriel Bédubourg, Léo Bouscarrat, et al.
Language Resources and Evaluation (2024)
Closed Access | Times Cited: 2
Fighting Against the Repetitive Training and Sample Dependency Problem in Few-Shot Named Entity Recognition
Chang Tian, Wenpeng Yin, Dan Li, et al.
IEEE Access (2024) Vol. 12, pp. 37600-37614
Open Access | Times Cited: 2
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