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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:

Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
Sewon Min, Xinxi Lyu, Ari Holtzman, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 378

Showing 1-25 of 378 citing articles:

Learning To Retrieve Prompts for In-Context Learning
Ohad Rubin, Jonathan Herzig, Jonathan Berant
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2022)
Open Access | Times Cited: 207
Large language models are few-shot clinical information extractors
Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 173
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
Mirac Süzgün, Nathan Scales, Nathanael Schärli, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2023)
Open Access | Times Cited: 97
Can language models learn from explanations in context?
Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, et al.
(2022)
Open Access | Times Cited: 85
A Survey on Multimodal Large Language Models for Autonomous Driving
Can Cui, Yunsheng Ma, Xu Cao, et al.
(2024), pp. 958-979
Open Access | Times Cited: 83
Auditing large language models: a three-layered approach
Jakob Mökander, Jonas Schuett, Hannah Rose Kirk, et al.
AI and Ethics (2023) Vol. 4, Iss. 4, pp. 1085-1115
Open Access | Times Cited: 81
RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning
Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 79
GPT-RE: In-context Learning for Relation Extraction using Large Language Models
Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 77
Reasoning with Language Model Prompting: A Survey
Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.
(2023)
Open Access | Times Cited: 68
Towards Mitigating LLM Hallucination via Self Reflection
Ziwei Ji, Tiezheng Yu, Yan Xu, et al.
(2023)
Open Access | Times Cited: 64
GPT-3-Driven Pedagogical Agents to Train Children’s Curious Question-Asking Skills
Rania Abdelghani, Yen-Hsiang Wang, Xingdi Yuan, et al.
International Journal of Artificial Intelligence in Education (2023) Vol. 34, Iss. 2, pp. 483-518
Closed Access | Times Cited: 55
Personality Traits in Large Language Models
Gregory Serapio‐García, Mustafa Safdari, Clément Crepy, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 52
Prompting PaLM for Translation: Assessing Strategies and Performance
David Vilar, Markus Freitag, Colin Cherry, et al.
(2023)
Open Access | Times Cited: 47
When large language models meet personalization: perspectives of challenges and opportunities
Jing Chen, Zheng Liu, Xu Huang, et al.
World Wide Web (2024) Vol. 27, Iss. 4
Open Access | Times Cited: 44
Dynamic prompt-based virtual assistant framework for BIM information search
Junwen Zheng, Martin Fischer
Automation in Construction (2023) Vol. 155, pp. 105067-105067
Closed Access | Times Cited: 42
Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters
Boshi Wang, Sewon Min, Xiang Deng, et al.
(2023)
Open Access | Times Cited: 41
GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models
Archiki Prasad, Peter Hase, Xiang Zhou, et al.
(2023)
Open Access | Times Cited: 41
A Survey of Large Language Models for Healthcare: From Data, Technology, and Applications to Accountability and Ethics
Kai He, Rui Mao, Qika Lin, et al.
(2024)
Open Access | Times Cited: 40
An Empirical Evaluation of Prompting Strategies for Large Language Models in Zero-Shot Clinical Natural Language Processing: Algorithm Development and Validation Study
Sonish Sivarajkumar, Mark Kelley, Alyssa Samolyk-Mazzanti, et al.
JMIR Medical Informatics (2024) Vol. 12, pp. e55318-e55318
Open Access | Times Cited: 36
A survey of safety and trustworthiness of large language models through the lens of verification and validation
Xiaowei Huang, Wenjie Ruan, Wei Huang, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 7
Open Access | Times Cited: 30
GRACE: Empowering LLM-based software vulnerability detection with graph structure and in-context learning
Guilong Lu, Xiaolin Ju, Xiang Chen, et al.
Journal of Systems and Software (2024) Vol. 212, pp. 112031-112031
Closed Access | Times Cited: 24
Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Models
Antoine Louis, Gijs van Dijck, Gerasimos Spanakis
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 20, pp. 22266-22275
Open Access | Times Cited: 22
GraphGPT: Graph Instruction Tuning for Large Language Models
Jiabin Tang, Yuhao Yang, Wei Wei, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2024), pp. 491-500
Open Access | Times Cited: 21
Foundation Models
J. Schneider, Christian Meske, Pauline Kuss
Business & Information Systems Engineering (2024) Vol. 66, Iss. 2, pp. 221-231
Open Access | Times Cited: 18
A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics
Kai He, Rui Mao, Qika Lin, et al.
Information Fusion (2025), pp. 102963-102963
Open Access | Times Cited: 6
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