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Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and concern among software engineers.
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Hadas Orgad and Yonatan Belinkov. 2022 · 2022
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How Gender Debiasing Affects Internal Model Representations, and Why It Matters. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022 . 2602–2628
Hadas Orgad, Seraphina Goldfarb-Tarrant, and Yonatan Belinkov. 2022 · 2022
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A combinatorial approach to fairness testing of machine learning models. In Proceedings of the 15th IEEE International Conference on Software Testing, Verification and Validation Workshops ICST Workshops 2022 . 94–101
Ankita Ramjibhai Patel, Jaganmohan Chandrasekaran, Yu Lei, Raghu N. Kacker, and D. Richard Kuhn. 2022 · 2022
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Search-based fairness testing for regression-based machine learning systems
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A Review on Fairness in Machine Learning
Dana Pessach and Erez Shmueli. 2022 · 2022
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Fairness Evaluation in Deepfake Detection Models using Metamorphic Testing. In Proceedings of the IEEE/ACM 7th International Workshop on Metamorphic Testing, MET@ICSE 2022 . 7–14
Muxin Pu, Meng Yi Kuan, Nyee Thoang Lim, Chun Yong Chong, and Mei Kuan Lim. 2022 · 2022
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AequeVox: Automated Fairness Testing of Speech Recognition Systems. In Proceedings of the 25th International Conference on Fundamental Approaches to Software Engineering, FASE 2022 . 245–267
Sai Sathiesh Rajan, Sakshi Udeshi, and Sudipta Chattopadhyay. 2022 · 2022
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An efficient discrimination discovery method for fairness testing. In Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering, SEKE 2022 . 200–205
Shinya Sano, Takashi Kitamura, and Shingo Takada. 2022 · 2022
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To make AI fair, here’s what we must learn to do
Mona Sloane. 2022 · 2022
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“I’m sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor Dataset. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022 . 9180–9211
Eric Michael Smith, Melissa Hall, Melanie Kambadur, Eleonora Presani, and Adina Williams. 2022 · 2022
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ASTRAEA: Grammar-based Fairness Testing
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Software Fairness: An Analysis and Survey
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The Effect of Model Compression on Fairness in Facial Expression Recognition. In Proceedings of Workshop on Applied Affect Recognition at the 26th International Conference on Pattern Recognition, ICPR 2022
Samuil Stoychev and Hatice Gunes. 2022 · 2022
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Causality-Based Neural Network Repair. In Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, ICSE 2022 . 338–349
Bing Sun, Jun Sun, Long H. Pham, and Tie Shi. 2022a · 2022
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Improving Machine Translation Systems via Isotopic Replacement. In Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, ICSE 2022 . 1181–1192
Zeyu Sun, Jie M. Zhang, Yingfei Xiong, Mark Harman, Mike Papadakis, and Lu Zhang. 2022b · 2022
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RULER: Discriminative and Iterative Adversarial Training for Deep Neural Network Fairness. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022 . 1173–1184
Guanhong Tao, Weisong Sun, Tingxu Han, Chunrong Fang, and Xiangyu Zhang. 2022 · 2022
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Fairness-aware Configuration of Machine Learning Libraries. In Proceedings of the 44th International Conference on Software Engineering, ICSE 2022
Saeid Tizpaz-Niari, Ashish Kumar, Gang Tan, and Ashutosh Trivedi. 2022 · 2022
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A Systematic Literature Review of Anti-Discrimination Design Strategies in the Digital Sharing Economy
Miroslav Tushev, Fahimeh Ebrahimi, and Anas M Mahmoud. 2022 · 2022
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EAGLE: Creating Equivalent Graphs to Test Deep Learning Libraries. In Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, ICSE 2022 . 798–810
Jiannan Wang, Thibaud Lutellier, Shangshu Qian, Hung Viet Pham, and Lin Tan. 2022a · 2022
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Jun Wang, Benjamin I. P. Rubinstein, and Trevor Cohn. 2022b · 2022
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Can Model Compression Improve NLP Fairness
Guangxuan Xu and Qingyuan Hu. 2022 · 2022
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Enhancing Fairness in Face Detection in Computer Vision Systems by Demographic Bias Mitigation. In Proceedings of AAAI/ACM Conference on AI, Ethics, and Society, AIES 2022 . 813–822
Yu Yang, Aayush Gupta, Jianwei Feng, Prateek Singhal, Vivek Yadav, Yue Wu, Pradeep Natarajan, Varsha Hedau, and Jungseock Joo. 2022 · 2022
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Fair Decision Making via Automated Repair of Decision Trees. In Proceedings of the 2nd IEEE/ACM International Workshop on Equitable Data & Technology, FairWare@ICSE 2022 . 9–16
Jiang Zhang, Ivan Beschastnikh, Sergey Mechtaev, and Abhik Roychoudhury. 2022a · 2022
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Machine Learning Testing: Survey, Landscapes and Horizons
Jie M. Zhang, Mark Harman, Lei Ma, and Yang Liu. 2022b · 2022
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Adaptive Fairness Improvement based on Causality Analysis. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022 . 6–17
Mengdi Zhang and Jun Sun. 2022 · 2022
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Efficient Fairness Testing Through Hash-Based Sampling. In Proceedings of the 14th International Symposium on Search-Based Software Engineering, SSBSE 2022 . 35–50
Zhenjiang Zhao, Takahisa Toda, and Takashi Kitamura. 2022 · 2022
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NeuronFair - Interpretable White-Box Fairness Testing through Biased Neuron Identification. In Proceedings of the 44th International Conference on Software Engineering, ICSE 2022
Haibin Zheng, Zhiqing Chen, Tianyu Du, Xuhong Zhang, Yao Cheng, Shouling Ji, Jingyi Wang, Yue Yu, and Jinyin Chen. 2022 · 2022
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BiasAsker
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FairEnsembles
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Fairlearn
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FairMask
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How should AI systems behave, and who should decide?
2023 · 2023
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Understanding fairness requirements for ML-based software. In Proceedings of the 31st IEEE International Requirements Engineering Conferece, RE 2023 . 341–346
Luciano Baresi, Chiara Criscuolo, and Carlo Ghezzi. 2023 · 2023
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A comprehensive empirical study of bias mitigation methods for machine learning classifiers
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Towards understanding fairness and its composition in ensemble machine learning. In Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, ICSE 2023
Usman Gohar, Sumon Biswas, and Hridesh Rajan. 2023 · 2023
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A Survey on Intersectional Fairness in Machine Learning: Notions, Mitigation, and Challenges. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI 2023 . 6619–6627
Usman Gohar and Lu Cheng. 2023 · 2023
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FairRec: Fairness testing for deep recommender systems. In Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2023
Huizhong Guo, Jinfeng Li, Jingyi Wang, Xiangyu Liu, Dongxia Wang, Zehong Hu, Rong Zhang, and Hui Xue. 2023 · 2023
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Bias mitigation for machine learning classifiers: A comprehensive survey
Max Hort, Zhenpeng Chen, Jie M. Zhang, Federica Sarro, and Mark Harman. 2023 · 2023
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A survey on fairness in large language models
Yingji Li, Mengnan Du, Rui Song, Xin Wang, and Ying Wang. 2023 · 2023
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Information-theoretic testing and debugging of fairness defects in deep neural networks. In Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, ICSE 2023
Verya Monjezi, Ashutosh Trivedi, Gang Tan, and Saeid Tizpaz-Niari. 2023 · 2023
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FairMask: Better Fairness via Model-based Rebalancing of Protected Attributes
Kewen Peng, Joymallya Chakraborty, and Tim Menzies. 2023 · 2023
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Search-Based Software Engineering in the Era of Modern Software Systems. In Proceedings of the 31st IEEE International Requirements Engineering Conferece . IEEE
Federica Sarro. 2023 · 2023
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BiasAsker: Measuring the Bias in Conversational AI System. In Proceedings of the 31st ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2023
Yuxuan Wan, Wenxuan Wang, Pinjia He, Jiazhen Gu, Haonan Bai, and Michael R. Lyu. 2023 · 2023
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Latent imitator: Generating natural individual discriminatory instances for black-box fairness testing. In Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis, ISSTA 2023
Yisong Xiao, Aishan Liu, Tianlin Li, and Xianglong Liu. 2023 · 2023
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TESTSGD: Interpretable testing of neural networks against subtle group discrimination
Mengdi Zhang, Jun Sun, Jingyi Wang, and Bing Sun. 2023 · 2023
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Fairness improvement with multiple protected attributes: How far are we?. In Proceedings of the 46th ACM/IEEE International Conference on Software Engineering, ICSE 2024
Zhenpeng Chen, Jie M. Zhang, Federica Sarro, and Mark Harman. 2024 · 2024
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Causal Modeling-Based Discrimination Discovery and Removal: Criteria, Bounds, and Algorithms
Lu Zhang, Yongkai Wu, and Xintao Wu. 2019a · 2050
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