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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.

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Showing 26-50 of 86 citing articles:

Towards Generalized Methods for Automatic Question Generation in Educational Domains
Huy A. Nguyen, Shravya Bhat, Steven Moore, et al.
Lecture notes in computer science (2022), pp. 272-284
Closed Access | Times Cited: 19
A Prompt-Based Topic-Modeling Method for Depression Detection on Low-Resource Data
Yanrong Guo, Jilong Liu, Lei Wang, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 11, Iss. 1, pp. 1430-1439
Closed Access | Times Cited: 12
Uncovering the Causes of Emotions in Software Developer Communication Using Zero-shot LLMs
Mia Mohammad Imran, Preetha Chatterjee, Kostadin Damevski
(2024), pp. 1-13
Open Access | Times Cited: 4
MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning
Bohan Li, Longxu Dou, Yutai Hou, et al.
International Journal of Machine Learning and Cybernetics (2025)
Closed Access
The Optimization of Advertising Content and Prediction of Consumer Response Rate Based on Generative Adversarial Networks
Changlin Wang, Zhonghua Lu, Z. Y. He
Journal of Organizational and End User Computing (2025) Vol. 37, Iss. 1, pp. 1-30
Open Access
Arabic Short‐Text Dataset for Sentiment Analysis of Tourism and Leisure Events
Seham Basabain, Ahmed Al‐Dubai, Erik Cambria, et al.
Expert Systems (2025) Vol. 42, Iss. 5
Open Access
Finetuned Language Models Are Zero-Shot Learners
Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 25
In-BoXBART: Get Instructions into Biomedical Multi-Task Learning
Mihir Parmar, Swaroop Mishra, Mirali Purohit, et al.
Findings of the Association for Computational Linguistics: NAACL 2022 (2022)
Open Access | Times Cited: 17
Towards Unified Prompt Tuning for Few-shot Text Classification
Jianing Wang, Chengyu Wang, Fuli Luo, et al.
(2022), pp. 524-536
Open Access | Times Cited: 17
InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuning
Prakhar Gupta, Cathy Jiao, Yi‐Ting Yeh, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022), pp. 505-525
Open Access | Times Cited: 16
ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval
Yue Yu, Yuchen Zhuang, Rongzhi Zhang, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2023)
Open Access | Times Cited: 10
Generative Speech Recognition Error Correction With Large Language Models and Task-Activating Prompting
Chao-Han Huck Yang, Yile Gu, Yi-Chieh Liu, et al.
2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) (2023)
Open Access | Times Cited: 10
Large Language Model Instruction Following: A Survey of Progresses and Challenges
Renze Lou, Kai Zhang, Wenpeng Yin
Computational Linguistics (2024), pp. 1-43
Open Access | Times Cited: 3
GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning
Haiteng Zhao, Shengchao Liu, Chang Ma, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 8
How Many Data Samples is an Additional Instruction Worth?
Ravsehaj Singh Puri, Swaroop Mishra, Mihir Parmar, et al.
(2023), pp. 1042-1057
Open Access | Times Cited: 8
Soft Prompt Decoding for Multilingual Dense Retrieval
Zhiqi Huang, Hansi Zeng, Hamed Zamani, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2023), pp. 1208-1218
Open Access | Times Cited: 7
Parallel Learning for Legal Intelligence: A HANOI Approach Based on Unified Prompting
Zhuoyang Song, Min Huang, Qinghai Miao, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 11, Iss. 2, pp. 2765-2775
Closed Access | Times Cited: 7
Explaining Data Patterns in Natural Language with Language Models
Chandan Singh, John X. Morris, Jyoti Aneja, et al.
(2023)
Open Access | Times Cited: 7
Exploring Universal Intrinsic Task Subspace for Few-Shot Learning via Prompt Tuning
Yujia Qin, Xiaozhi Wang, Yusheng Su, et al.
IEEE/ACM Transactions on Audio Speech and Language Processing (2024) Vol. 32, pp. 3631-3643
Open Access | Times Cited: 2
LLMs in the Loop: Leveraging Large Language Model Annotations for Active Learning in Low-Resource Languages
Nataliia Kholodna, Sahib Julka, Mohammad Khodadadi, et al.
Lecture notes in computer science (2024), pp. 397-412
Closed Access | Times Cited: 2
Improving In-Context Few-Shot Learning via Self-Supervised Training
Mingda Chen, Jingfei Du, Ramakanth Pasunuru, 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: 12
HELP ME THINK: A Simple Prompting Strategy for Non-experts to Create Customized Content with Models
Swaroop Mishra, Elnaz Nouri
Findings of the Association for Computational Linguistics: ACL 2022 (2023), pp. 11834-11890
Open Access | Times Cited: 6
Efficient (Soft) Q-Learning for Text Generation with Limited Good Data
Han Guo, Bowen Tan, Zhengzhong Liu, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 13
Transforming Sequence Tagging Into A Seq2Seq Task
Karthik Raman, Iftekhar Naim, Jiecao Chen, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 9
Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning?
Chengwei Qin, Shafiq Joty, Qian Li, et al.
(2023), pp. 11802-11832
Open Access | Times Cited: 5

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