X-Hacking: The Threat of Misguided AutoML

Citations

Showing 8 citing works with retrievable metadata.

• Systemizing Multiplicity: The Curious Case of Arbitrariness in Machine Learning
  Prakhar Ganesh, Afaf Taik, Golnoosh Farnadi · 2025 · Proceedings of the AAAI/ACM Conference on AI Ethics and Society
• Integrating AutoML and Explainability
  Ayush Dalmia, Chandramohan Dhasarathan · 2026 · Wiley eBooks
• When Explanations Deceive: Understanding Unintentional and Intentional Deception in XAI
  Sule Tekkesinoglu · 2026 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
• Equally Good, Yet Different: Benchmarking Rashomon sets in AutoML packages
  Katarzyna Woźnica, Katarzyna Rogalska, Zuzanna Sieńko, et al. · 2026
• Auto-EAD: An Automated Ensemble Anomaly Detection Framework for the CEN-IoT
  Lei Ding, Wen-Li Shang, Shuang Wang, et al. · 2026 · IEEE transactions on consumer electronics
• Informative Post-Hoc Explanations Only Exist for Simple Functions
  Eric Günther, Balázs Szabados, Robi Bhattacharjee, et al. · 2025 · arXiv.org
• CleanSurvival: automated data preprocessing for time-to-event models using reinforcement learning
  Yousef Koka, David Antony Selby, Gerrit Großmann, et al. · 2025 · BMC Medical Informatics and Decision Making
• Position: Rethinking Explainable Machine Learning as Applied Statistics
  Sebastian Bordt, Eric Raidl, U. von Luxburg · 2024 · International Conference on Machine Learning