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On the robustness of sparse counterfactual explanations to adverse perturbations
Artificial Intelligence 316 (C):103840 (2023)
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Citations of this work
Nullius in Explanans: an ethical risk assessment for explainable AI.Luca Nannini, Diletta Huyskes, Enrico Panai, Giada Pistilli & Alessio Tartaro - 2025 - Ethics and Information Technology 27 (1):1-28.
Interval abstractions for robust counterfactual explanations.Junqi Jiang, Francesco Leofante, Antonio Rago & Francesca Toni - 2024 - Artificial Intelligence 336 (C):104218.
References found in this work
The global landscape of AI ethics guidelines.A. Jobin, M. Ienca & E. Vayena - 2019 - Nature Machine Intelligence 1.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.Cynthia Rudin - 2019 - Nature Machine Intelligence 1.
Peeking inside the black-box: A survey on explainable artificial intelligence (XAI).A. Adadi & M. Berrada - 2018 - IEEE Access 6.
A Survey of Methods for Explaining Black Box Models.Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri, Franco Turini, Fosca Giannotti & Dino Pedreschi - 2019 - ACM Computing Surveys 51 (5):1-42.
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