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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:

TruthfulQA: Measuring How Models Mimic Human Falsehoods
Stephanie Lin, Jacob Hilton, Owain Evans
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022)
Open Access | Times Cited: 162

Showing 1-25 of 162 citing articles:

Survey of Hallucination in Natural Language Generation
Ziwei Ji, Nayeon Lee, Rita Frieske, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 12, pp. 1-38
Open Access | Times Cited: 1229
A Survey on Evaluation of Large Language Models
Yupeng Chang, Xu Wang, Jindong Wang, et al.
ACM Transactions on Intelligent Systems and Technology (2024) Vol. 15, Iss. 3, pp. 1-45
Open Access | Times Cited: 483
ChatGPT makes medicine easy to swallow: an exploratory case study on simplified radiology reports
Katharina Jeblick, Balthasar Schachtner, Jakob Dexl, et al.
European Radiology (2023) Vol. 34, Iss. 5, pp. 2817-2825
Open Access | Times Cited: 302
Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine
Stefan Harrer
EBioMedicine (2023) Vol. 90, pp. 104512-104512
Open Access | Times Cited: 248
A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly
Yifan Yao, Jinhao Duan, Kaidi Xu, et al.
High-Confidence Computing (2024) Vol. 4, Iss. 2, pp. 100211-100211
Open Access | Times Cited: 140
QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension
Anna Rogers, Matt Gardner, Isabelle Augenstein
ACM Computing Surveys (2022) Vol. 55, Iss. 10, pp. 1-45
Open Access | Times Cited: 106
In-Context Retrieval-Augmented Language Models
Ori Ram, Yoav Levine, Itay Dalmedigos, et al.
Transactions of the Association for Computational Linguistics (2023) Vol. 11, pp. 1316-1331
Open Access | Times Cited: 87
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: 86
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: 74
Foundation metrics for evaluating effectiveness of healthcare conversations powered by generative AI
Mahyar Abbasian, Elahe Khatibi, Iman Azimi, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 41
AI deception: A survey of examples, risks, and potential solutions
Peter S. Park, Simon Goldstein, Aidan O’Gara, et al.
Patterns (2024) Vol. 5, Iss. 5, pp. 100988-100988
Open Access | Times Cited: 37
Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models
Matthew Dahl, Varun Magesh, Mirac Suzgun, et al.
The Journal of Legal Analysis (2024) Vol. 16, Iss. 1, pp. 64-93
Open Access | Times Cited: 28
Beware of botshit: How to manage the epistemic risks of generative chatbots
Timothy R. Hannigan, Ian P. McCarthy, André Spicer
Business Horizons (2024) Vol. 67, Iss. 5, pp. 471-486
Closed Access | Times Cited: 24
SEED-Bench: Benchmarking Multimodal Large Language Models
Bohao Li, Yuying Ge, Yixiao Ge, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 33, pp. 13299-13308
Closed Access | Times Cited: 21
Combating misinformation in the age of LLMs: Opportunities and challenges
Canyu Chen, Kai Shu
AI Magazine (2024) Vol. 45, Iss. 3, pp. 354-368
Open Access | Times Cited: 17
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: 16
On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)
Gengchen Mai, Weiming Huang, Jin Sun, et al.
ACM Transactions on Spatial Algorithms and Systems (2024) Vol. 10, Iss. 2, pp. 1-46
Open Access | Times Cited: 16
Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies
Liangming Pan, Michael Saxon, Wenda Xu, et al.
Transactions of the Association for Computational Linguistics (2024) Vol. 12, pp. 484-506
Open Access | Times Cited: 14
Defining intelligence: Bridging the gap between human and artificial perspectives
Gilles E. Gignac, Eva T. Szodorai
Intelligence (2024) Vol. 104, pp. 101832-101832
Open Access | Times Cited: 13
Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding
Sicong Leng, Hang Zhang, Guanzheng Chen, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 35, pp. 13872-13882
Closed Access | Times Cited: 13
How to train your stochastic parrot: large language models for political texts
Joseph T. Ornstein, Elise Blasingame, Jake S. Truscott
Political Science Research and Methods (2025), pp. 1-18
Open Access | Times Cited: 2
Unsolved Problems in ML Safety
Dan Hendrycks, Nicholas Carlini, John Schulman, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 73
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: 35
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: 31
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback
Katherine Tian, Eric Mitchell, Allan Zhou, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 25
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