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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:

Interpretable Data-Based Explanations for Fairness Debugging
Romila Pradhan, Jiongli Zhu, Boris Glavic, et al.
Proceedings of the 2022 International Conference on Management of Data (2022), pp. 247-261
Open Access | Times Cited: 31

Showing 1-25 of 31 citing articles:

The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, et al.
2022 ACM Conference on Fairness, Accountability, and Transparency (2022), pp. 1194-1206
Open Access | Times Cited: 43
A Critical Survey on Fairness Benefits of Explainable AI
Luca Deck, Jakob Schoeffer, Maria De‐Arteaga, et al.
2022 ACM Conference on Fairness, Accountability, and Transparency (2024)
Open Access | Times Cited: 7
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models
Esma Balkır, Svetlana Kiritchenko, Isar Nejadgholi, et al.
(2022)
Open Access | Times Cited: 28
MisDetect: Iterative Mislabel Detection using Early Loss
Y DENG, Chengliang Chai, Lei Cao, et al.
Proceedings of the VLDB Endowment (2024) Vol. 17, Iss. 6, pp. 1159-1172
Closed Access | Times Cited: 4
A Roadmap of Explainable Artificial Intelligence: Explain to Whom, When, What and How?
Ziming Wang, Changwu Huang, Xin Yao
ACM Transactions on Autonomous and Adaptive Systems (2024) Vol. 19, Iss. 4, pp. 1-40
Open Access | Times Cited: 3
Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making
Shubha Guha, Falaah Arif Khan, Julia Stoyanovich, et al.
IEEE Transactions on Knowledge and Data Engineering (2024) Vol. 36, Iss. 12, pp. 7368-7379
Closed Access | Times Cited: 2
Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks
Zhenzhong Wang, Zeng Qing-yuan, Wanyu Lin, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 19, pp. 21690-21698
Open Access | Times Cited: 2
On Explaining Confounding Bias
Brit Youngmann, Michael Cafarella, Yuval Moskovitch, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2023), pp. 1846-1859
Open Access | Times Cited: 6
On Data-Aware Global Explainability of Graph Neural Networks
Ge Lv, Lei Chen
Proceedings of the VLDB Endowment (2023) Vol. 16, Iss. 11, pp. 3447-3460
Open Access | Times Cited: 6
IDE: A System for Iterative Mislabel Detection
Y DENG, Qiyan Deng, Chengliang Chai, et al.
(2024), pp. 500-503
Open Access | Times Cited: 2
Data journeys: Explaining AI workflows through abstraction
Enrico Daga, Paul Groth
Semantic Web (2023) Vol. 15, Iss. 4, pp. 1057-1083
Open Access | Times Cited: 5
A Unified Approach for Resilience and Causal Responsibility with Integer Linear Programming (ILP) and LP Relaxations
Neha Makhija, Wolfgang Gatterbauer
Proceedings of the ACM on Management of Data (2023) Vol. 1, Iss. 4, pp. 1-27
Open Access | Times Cited: 4
Towards Interactively Improving ML Data Preparation Code via "Shadow Pipelines"
Stefan Grafberger, Paul Groth, Sebastian Schelter
(2024), pp. 7-11
Open Access | Times Cited: 1
On Explaining Unfairness: An Overview
Christos Fragkathoulas, Vasiliki Papanikou, Danae Pla Karidi, et al.
(2024) Vol. 9, pp. 226-236
Open Access | Times Cited: 1
CAMO: Explaining Consensus Across MOdels
Andy C. Yu, Parke Godfrey, Lukasz Golab, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2024), pp. 5493-5496
Closed Access | Times Cited: 1
Explaining GNN-Based Recommendations in Logic
Wenfei Fan, Lihang Fan, Dandan Lin, et al.
Proceedings of the VLDB Endowment (2024) Vol. 18, Iss. 3, pp. 715-728
Closed Access | Times Cited: 1
A Critical Survey on Fairness Benefits of XAI
Luca Deck, Jakob Schoeffer, Maria De‐Arteaga, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 3
Proceedings of the 2nd Workshop on Trustworthy Natural Language Processing (TrustNLP 2022)

(2022)
Open Access | Times Cited: 5
Revisiting Lightweight Compiler Provenance Recovery on ARM Binaries
Jason Z. Kim, Daniel Genkin, Kevin Leach
(2023), pp. 292-303
Open Access | Times Cited: 2
Automated Data Cleaning Can Hurt Fairness in Machine Learning-based Decision Making
Shubha Guha, Falaah Arif Khan, Julia Stoyanovich, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2023), pp. 3747-3754
Closed Access | Times Cited: 2
Causal Inference in Data Analysis with Applications to Fairness and Explanations
Sudeepa Roy, Babak Salimi
Lecture notes in computer science (2023), pp. 105-131
Closed Access | Times Cited: 1
Exploring Fairness-Accuracy Trade-Offs in Binary Classification: A Comparative Analysis Using Modified Loss Functions
C. Trotter, Yixin Chen
(2024), pp. 148-156
Closed Access
Counterfactual Explanation at Will, with Zero Privacy Leakage
Shuai An, Yang Cao
Proceedings of the ACM on Management of Data (2024) Vol. 2, Iss. 3, pp. 1-29
Open Access
Enhancing the Rationale-Input Alignment for Self-explaining Rationalization
Wei Liu, Haozhao Wang, Jun Wang, et al.
2022 IEEE 38th International Conference on Data Engineering (ICDE) (2024), pp. 2218-2230
Open Access
Mutual Information-Based Counterfactuals for Fair Graph Neural Networks
Long Chen, Wenzhuo Chen, Jiayi Li, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2024) Vol. 24, pp. 1-8
Closed Access
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