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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:

RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models
Samuel Gehman, Suchin Gururangan, Maarten Sap, et al.
(2020)
Open Access | Times Cited: 411

Showing 51-75 of 411 citing articles:

Robot Autonomy vs. Human Autonomy: Social Robots, Artificial Intelligence (AI), and the Nature of Autonomy
Paul Formosa
Minds and Machines (2021) Vol. 31, Iss. 4, pp. 595-616
Open Access | Times Cited: 61
COLD: A Benchmark for Chinese Offensive Language Detection
Jiawen Deng, Jingyan Zhou, Hao Sun, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 50
Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning
Yasaman Razeghi, Robert L. Logan, Matt Gardner, et al.
(2022)
Open Access | Times Cited: 49
Controllable Natural Language Generation with Contrastive Prefixes
Qian Jing, Dong Li, Yelong Shen, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2022), pp. 2912-2924
Open Access | Times Cited: 48
DEMix Layers: Disentangling Domains for Modular Language Modeling
Suchin Gururangan, Mike Lewis, Ari Holtzman, 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: 47
The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems
Caleb Ziems, Jane Yu, Yi‐Chia Wang, et al.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022), pp. 3755-3773
Open Access | Times Cited: 47
On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark
Hao Sun, Guangxuan Xu, Jiawen Deng, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2022), pp. 3906-3923
Open Access | Times Cited: 44
You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual Settings
Zeerak Talat, Aurélie Névéol, Stella Biderman, et al.
(2022)
Open Access | Times Cited: 44
On Second Thought, Let’s Not Think Step by Step! Bias and Toxicity in Zero-Shot Reasoning
Omar Shaikh, Hongxin Zhang, William A. Held, et al.
(2023)
Open Access | Times Cited: 39
Language Model Behavior: A Comprehensive Survey
Tyler A. Chang, Benjamin Bergen
Computational Linguistics (2023) Vol. 50, Iss. 1, pp. 293-350
Open Access | Times Cited: 39
On the Globalization of the QAnon Conspiracy Theory Through Telegram
Mohamad Hoseini, Philipe Melo, Fabrí­cio Benevenuto, et al.
(2023), pp. 75-85
Open Access | Times Cited: 33
Towards Designing a ChatGPT Conversational Companion for Elderly People
Abeer Alessa, Hend S. Al‐Khalifa
(2023), pp. 667-674
Open Access | Times Cited: 33
Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors Persist
Marzena Karpinska, Mohit Iyyer
(2023)
Open Access | Times Cited: 33
Who Answers It Better? An In-Depth Analysis of ChatGPT and Stack Overflow Answers to Software Engineering Questions
Samia Kabir, David N. Udo-Imeh, Bonan Kou, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 32
Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey
Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.
(2023)
Open Access | Times Cited: 26
We’re Afraid Language Models Aren’t Modeling Ambiguity
Alisa Liu, Zhaofeng Wu, Julian Michael, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023), pp. 790-807
Open Access | Times Cited: 25
A Review of Current Trends, Techniques, and Challenges in Large Language Models (LLMs)
Rajvardhan Patil, And Venkat Gudivada
(2024)
Open Access | Times Cited: 16
Error Correction and Adaptation in Conversational AI: A Review of Techniques and Applications in Chatbots
Saadat Izadi, Mohamad Forouzanfar
AI (2024) Vol. 5, Iss. 2, pp. 803-841
Open Access | Times Cited: 15
Augmenting research methods with foundation models and generative AI
Sippo Rossi, Matti Rossi, Raghava Rao Mukkamala, et al.
International Journal of Information Management (2024) Vol. 77, pp. 102749-102749
Closed Access | Times Cited: 14
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance
Wenqi Wei, Ling Liu
ACM Computing Surveys (2024)
Open Access | Times Cited: 14
Navigating the challenges of generative technologies: Proposing the integration of artificial intelligence and blockchain
Jordan Brewer, Dhru Patel, Dennie Kim, et al.
Business Horizons (2024) Vol. 67, Iss. 5, pp. 525-535
Closed Access | Times Cited: 10
Digital forgetting in large language models: a survey of unlearning methods
Alberto Blanco-Justicia, Najeeb Moharram Jebreel, Benet Manzanares-Salor, et al.
Artificial Intelligence Review (2025) Vol. 58, Iss. 3
Open Access | Times Cited: 1
A Review of the Challenges with Massive Web-Mined Corpora Used in Large Language Models Pre-training
Michał Perełkiewicz, Rafał Poświata
Lecture notes in computer science (2025), pp. 153-163
Closed Access | Times Cited: 1
Detoxifying Language Models Risks Marginalizing Minority Voices
Albert Xu, Eshaan Pathak, Eric Wallace, et al.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
Open Access | Times Cited: 52
Probing Toxic Content in Large Pre-Trained Language Models
Nedjma Ousidhoum, Xinran Zhao, Tianqing Fang, et al.
(2021)
Open Access | Times Cited: 52

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