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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:

Truncation Sampling as Language Model Desmoothing
John K. Hewitt, Christopher D. Manning, Percy Liang
(2022), pp. 3414-3427
Open Access | Times Cited: 18

Showing 18 citing articles:

Applying large language models and chain-of-thought for automatic scoring
Gyeong-Geon Lee, Ehsan Latif, Xuansheng Wu, et al.
Computers and Education Artificial Intelligence (2024) Vol. 6, pp. 100213-100213
Open Access | Times Cited: 38
From Turing to Transformers: A Comprehensive Review and Tutorial on the Evolution and Applications of Generative Transformer Models
Emma Yann Zhang, Adrian David Cheok, Zhigeng Pan, et al.
Sci (2023) Vol. 5, Iss. 4, pp. 46-46
Open Access | Times Cited: 13
Glitter or gold? Deriving structured insights from sustainability reports via large language models
Marco Bronzini, Carlo Nicolini, Bruno Lepri, et al.
EPJ Data Science (2024) Vol. 13, Iss. 1
Open Access | Times Cited: 4
Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent
Markus Freitag, Nitika Mathur, Chi-kiu Lo, et al.
(2023), pp. 578-628
Open Access | Times Cited: 6
Evaluating Large Language Models on Controlled Generation Tasks
Jiao Sun, Yufei Tian, Wangchunshu Zhou, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023)
Open Access | Times Cited: 6
From Turing to Transformers: A Comprehensive Review and Tutorial on the Evolution and Applications of Generative Transformer Models
Adrian David Cheok, Emma Yann Zhang
(2023)
Open Access | Times Cited: 4
Epsilon Sampling Rocks: Investigating Sampling Strategies for Minimum Bayes Risk Decoding for Machine Translation
Markus Freitag, Behrooz Ghorbani, Patrick Fernandes
(2023), pp. 9198-9209
Open Access | Times Cited: 4
It’s MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk
Amanda Bertsch, Alex Xie, Graham Neubig, et al.
(2023), pp. 108-122
Open Access | Times Cited: 3
Quality Estimation Using Minimum Bayes Risk
Subhajit Naskar, Daniel Deutsch, Markus Freitag
(2023), pp. 806-811
Open Access | Times Cited: 3
Benchmarking and Improving Text-to-SQL Generation under Ambiguity
Adithya Bhaskar, Tushar Tomar, Ashutosh Sathe, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023), pp. 7053-7074
Open Access | Times Cited: 2
Look-back Decoding for Open-Ended Text Generation
Nan Xu, Chunting Zhou, Aslı Çelikyılmaz, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023), pp. 1039-1050
Open Access | Times Cited: 2
A Topic-Constrained Sampling Method for Text Generation
Wenyi Ran, Jiaqiang Wan, Zhiqiang Wang, et al.
(2024), pp. 92-97
Closed Access
Stealing the Decoding Algorithms of Language Models
Ali Naseh, Kalpesh Krishna, Mohit Iyyer, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 1
Generating Text from Language Models
Afra Amini, Ryan Cotterell, John K. Hewitt, et al.
(2023), pp. 27-31
Open Access | Times Cited: 1
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 6: Tutorial Abstracts)
Yang Deng, Wenqiang Lei, Minlie Huang, et al.
(2023)
Open Access
Knowledge Graph Compression Enhances Diverse Commonsense Generation
EunJeong Hwang, Veronika Thost, Vered Shwartz, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023), pp. 558-572
Open Access
Penalty Decoding: Well Suppress the Self-Reinforcement Effect in Open-Ended Text Generation
Wen-Hong Zhu, Hongkun Hao, Rui Wang
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023), pp. 1218-1228
Open Access
Faster Minimum Bayes Risk Decoding with Confidence-based Pruning
Julius D. Cheng, Andreas Vlachos
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023), pp. 12473-12480
Open Access
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