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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:

HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks
Yuanyuan Chen, Boyang Li, Han Yu, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2021) Vol. 35, Iss. 8, pp. 7081-7089
Open Access | Times Cited: 20

Showing 20 citing articles:

Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond
Xuhong Li, Haoyi Xiong, Xingjian Li, et al.
Knowledge and Information Systems (2022) Vol. 64, Iss. 12, pp. 3197-3234
Open Access | Times Cited: 252
Training data influence analysis and estimation: a survey
Zayd Hammoudeh, Daniel Lowd
Machine Learning (2024) Vol. 113, Iss. 5, pp. 2351-2403
Open Access | Times Cited: 16
Natural Example-Based Explainability: A Survey
Antonin Poché, Lucas Hervier, Mohamed-Chafik Bakkay
Communications in computer and information science (2023), pp. 24-47
Closed Access | Times Cited: 12
A Survey of Computer Vision Technologies in Urban and Controlled-environment Agriculture
Jiayun Luo, Boyang Li, Cyril Leung
ACM Computing Surveys (2023) Vol. 56, Iss. 5, pp. 1-39
Open Access | Times Cited: 11
FedMUA: Exploring the Vulnerabilities of Federated Learning to Malicious Unlearning Attacks
Jian Chen, Ziyuan Lin, Wanyu Lin, et al.
IEEE Transactions on Information Forensics and Security (2025) Vol. 20, pp. 1665-1678
Closed Access
Conversational Explanations: Discussing Explainable AI with Non-AI Experts
Tong Zhang, Mengxin Zhang, Wei Yan Low, et al.
(2025), pp. 409-424
Closed Access
Data Glitches Discovery using Influence-based Model Explanations
Nikolaos Myrtakis, Ioannis Tsamardinos, Vassilis Christophides
(2025), pp. 1068-1079
Closed Access
Automatic Product Copywriting for E-commerce
Xueying Zhang, Yanyan Zou, Hainan Zhang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 11, pp. 12423-12431
Open Access | Times Cited: 15
Machine Unlearning for Random Forests
Jonathan Brophy, Daniel Lowd
arXiv (Cornell University) (2020)
Open Access | Times Cited: 23
Better, Not Just More: Data-centric machine learning for Earth observation
Ribana Roscher, Marc Rußwurm, Caroline Gevaert, et al.
IEEE Geoscience and Remote Sensing Magazine (2024), pp. 2-22
Open Access | Times Cited: 2
Energy efficient and optimized genetic algorithm for software effort estimator using double hidden layer bi-directional associative memory
Chandra Shekhar Yadav, Raghuraj Singh, Sambit Satpathy, et al.
Sustainable Energy Technologies and Assessments (2023) Vol. 56, pp. 102986-102986
Closed Access | Times Cited: 5
Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation
Zayd Hammoudeh, Daniel Lowd
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security (2022), pp. 1367-1381
Open Access | Times Cited: 7
May I Ask a Follow-up Question? Understanding the Benefits of Conversations in Neural Network Explainability
Tong Zhang, X. Jessie Yang, Boyang Li
International Journal of Human-Computer Interaction (2024), pp. 1-25
Open Access | Times Cited: 1
Rethinking Influence Functions of Neural Networks in the Over-Parameterized Regime
Rui Zhang, Shihua Zhang
Proceedings of the AAAI Conference on Artificial Intelligence (2022) Vol. 36, Iss. 8, pp. 9082-9090
Open Access | Times Cited: 5
Influence Functions for Sequence Tagging Models
Sarthak Jain, Varun Manjunatha, Byron Wallace, et al.
(2022), pp. 824-839
Open Access | Times Cited: 5
Automatic product copywriting for e‐commerce
Yanyan Zou, Xueying Zhang, Jing Zhou, et al.
AI Magazine (2023) Vol. 44, Iss. 1, pp. 41-53
Open Access | Times Cited: 2
Explainable AI (XAI) for Neonatal Pain Assessment via Influence Function Modification
Md. Imran Hossain, Ghada Zamzmi, Peter R. Mouton, et al.
(2024), pp. 1-5
Closed Access
Training Data Influence Analysis and Estimation: A Survey
Zayd Hammoudeh, Daniel Lowd
arXiv (Cornell University) (2022)
Open Access | Times Cited: 1
The model thinks what?! Interpreting deep NLP models with rationales and influence
Sarthak Jain
(2022)
Open Access
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime
Rui Zhang, Shihua Zhang
arXiv (Cornell University) (2021)
Open Access
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