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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:

Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 160

Showing 1-25 of 160 citing articles:

Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey
Bonan Min, Hayley Ross, Elior Sulem, et al.
ACM Computing Surveys (2023) Vol. 56, Iss. 2, pp. 1-40
Open Access | Times Cited: 558
Can Large Language Models Transform Computational Social Science?
Caleb Ziems, William A. Held, Omar Ahmed Shaikh, et al.
Computational Linguistics (2023) Vol. 50, Iss. 1, pp. 237-291
Open Access | Times Cited: 192
A comprehensive survey on pretrained foundation models: a history from BERT to ChatGPT
Ce Zhou, Qian Li, Chen Li, et al.
International Journal of Machine Learning and Cybernetics (2024)
Closed Access | Times Cited: 119
A survey of GPT-3 family large language models including ChatGPT and GPT-4
Katikapalli Subramanyam Kalyan
Natural Language Processing Journal (2023) Vol. 6, pp. 100048-100048
Open Access | Times Cited: 112
ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning
Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.
(2023)
Open Access | Times Cited: 99
One Embedder, Any Task: Instruction-Finetuned Text Embeddings
Hongjin Su, Weijia Shi, Jungo Kasai, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2023)
Open Access | Times Cited: 69
Using natural language processing to support peer‐feedback in the age of artificial intelligence: A cross‐disciplinary framework and a research agenda
Elisabeth Bauer, Martin Greisel, Ilia Kuznetsov, et al.
British Journal of Educational Technology (2023) Vol. 54, Iss. 5, pp. 1222-1245
Open Access | Times Cited: 65
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation
Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 52
When brain-inspired AI meets AGI
Lin Zhao, Lu Zhang, Zihao Wu, et al.
Meta-Radiology (2023) Vol. 1, Iss. 1, pp. 100005-100005
Open Access | Times Cited: 50
MEGA: Multilingual Evaluation of Generative AI
Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 46
Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!
Yubo Ma, Yixin Cao, Yong Sik Hong, et al.
(2023)
Open Access | Times Cited: 44
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
A Review of Current Trends, Techniques, and Challenges in Large Language Models (LLMs)
Rajvardhan Patil, Venkat N. Gudivada
Applied Sciences (2024) Vol. 14, Iss. 5, pp. 2074-2074
Open Access | Times Cited: 28
Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering
Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lù, et al.
Transactions of the Association for Computational Linguistics (2024) Vol. 12, pp. 681-699
Open Access | Times Cited: 27
Larger and more instructable language models become less reliable
Lexin Zhou, Wout Schellaert, Fernando Martínez‐Plumed, et al.
Nature (2024) Vol. 634, Iss. 8032, pp. 61-68
Open Access | Times Cited: 26
BLIVA: A Simple Multimodal LLM for Better Handling of Text-Rich Visual Questions
Wenbo Hu, Yifan Xu, Yi Li, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 3, pp. 2256-2264
Open Access | Times Cited: 22
Datasets for Large Language Models: A Comprehensive Survey
Yang Liu, Jiahuan Cao, Chongyu Liu, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 17
Towards building multilingual language model for medicine
Pengcheng Qiu, Chaoyi Wu, Xiaoman Zhang, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 15
Large language models for reticular chemistry
Zhiling Zheng, Nakul Rampal, Theo Jaffrelot Inizan, et al.
Nature Reviews Materials (2025)
Closed Access | Times Cited: 3
Generative AI meets Responsible AI: Practical Challenges and Opportunities
Krishnaram Kenthapadi, Himabindu Lakkaraju, Nazneen Fatema Rajani
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2023), pp. 5805-5806
Closed Access | Times Cited: 33
A fine-grained comparison of pragmatic language understanding in humans and language models
Jennifer J. Hu, Sammy Floyd, Olessia Jouravlev, et al.
(2023)
Open Access | Times Cited: 29
Artificial Intelligence Co-Piloted Auditing
Hanchi Gu, Marco Schreyer, Kevin Moffitt, et al.
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 28
PromptCap: Prompt-Guided Image Captioning for VQA with GPT-3
Yushi Hu, Hang Hua, Zhengyuan Yang, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2023), pp. 2951-2963
Closed Access | Times Cited: 23
Transfer learning for language model adaptation
Mehwish Bari
(2023)
Open Access | Times Cited: 22
The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning
Seungone Kim, Segyeong Joo, Doyoung Kim, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 22
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