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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:

Low-Complexity Probing via Finding Subnetworks
Steven Cao, Victor Sanh, Alexander M. Rush
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021), pp. 960-966
Open Access | Times Cited: 16

Showing 16 citing articles:

Parameter-Efficient Transfer Learning with Diff Pruning
Demi Guo, Alexander M. Rush, Yoon Kim
(2021)
Open Access | Times Cited: 151
The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems Fail
Samuel Bowman
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022)
Open Access | Times Cited: 40
Explaining Human Comparisons Using Alignment-Importance Heatmaps
N.P. Truong, Dario Pesenti, Uri Hasson
Computational Brain & Behavior (2025)
Open Access
Conditional probing: measuring usable information beyond a baseline
John Hewitt, Kawin Ethayarajh, Percy Liang, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021), pp. 1626-1639
Open Access | Times Cited: 23
Parameter-Efficient Transfer Learning with Diff Pruning
Demi Guo, Alexander M. Rush, Yoon Kim
arXiv (Cornell University) (2020)
Open Access | Times Cited: 16
Probing Classifiers: Promises, Shortcomings, and Advances
Yonatan Belinkov
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 6
Towards Extracting and Understanding the Implicit Rubrics of Transformer Based Automatic Essay Scoring Models
James Fiacco, David M. Adamson, Carolyn Ros
(2023), pp. 232-241
Open Access | Times Cited: 2
A multi-facet analysis of BERT-based entity matching models
Matteo Paganelli, Donato Tiano, Francesco Guerra
The VLDB Journal (2023) Vol. 33, Iss. 4, pp. 1039-1064
Closed Access | Times Cited: 2
SocioProbe: What, When, and Where Language Models Learn about Sociodemographics
Anne Lauscher, Federico Bianchi, Samuel R. Bowman, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022), pp. 7901-7918
Open Access | Times Cited: 4
When Combating Hype, Proceed with Caution.
Samuel R. Bowman
arXiv (Cornell University) (2021)
Closed Access | Times Cited: 3
How Does Adversarial Fine-Tuning Benefit BERT?
Javid Ebrahimi, Hao Yang, Wei Zhang
arXiv (Cornell University) (2021)
Open Access | Times Cited: 3
Attentional Probe: Estimating a Module’s Functional Potential
Tiago Pimentel, Josef Valvoda, Niklas Stoehr, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022), pp. 11459-11472
Open Access | Times Cited: 1
Exploratory Model Analysis Using Data-Driven Neuron Representations
Daisuke Oba, Naoki Yoshinaga, Masashi Toyoda
(2021), pp. 518-528
Open Access | Times Cited: 1
Visualizing the Relationship Between Encoded Linguistic Information and Task Performance
Jiannan Xiang, Huayang Li, Defu Lian, et al.
Findings of the Association for Computational Linguistics: ACL 2022 (2022), pp. 410-422
Open Access
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
Cheng-I Lai, Shuicheng Yan, Alexander H. Liu, et al.
arXiv (Cornell University) (2021)
Closed Access
Conditional probing: measuring usable information beyond a baseline
John Hewitt, Kawin Ethayarajh, Percy Liang, et al.
Empirical Methods in Natural Language Processing (2021), pp. 1626-1639
Closed Access
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