SoK Papers in IEEE Conference on Secure and Trustworthy Machine Learning
SoK Authors · Frequently Asked Questions ·
Other Conferences with SoK
| 2025 | |
| SoK: Fair Clustering: Critique, Caveats, and Future Directions | John Dickerson, Seyed Esmaeili, Jamie Morgenstern, Claire Jie Zhang |
| SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It) | Matthieu Meeus, Igor Shilov, Shubham Jain, Manuel Faysse, Marek Rei, Yves-Alexandre de Montjoye |
| SoK: On the Offensive Potential of AI | Saskia Laura Schröer, Giovanni Apruzzese, Soheil Human, Pavel Laskov, Hyrum S. Anderson, Edward W.N. Bernroider, Aurore Fass, Ben Nassi, Vera Rimmer, Fabio Roli, Samer Salam, Ashley Shen, Ali Sunyaev, Tim Wadhwa-Brown, Isabel Wagner, Gang Wang |
| SoK: What Makes Private Learning Unfair? | Kai Yao, Marc Juarez |
| 2024 | |
| SoK: A Review of Differentially Private Linear Models For High Dimensional Data | Amol Khanna, Edward Raff, Nathan Inkawhich |
| SoK: AI Auditing: The Broken Bus on the Road to AI Accountability | Abeba Birhane, Ryan Steed, Victor Ojewale, Briana Vecchione, Inioluwa Deborah Raji |
| SoK: Pitfalls in Evaluating Black-Box Attacks | Fnu Suya, Anshuman Suri, Tingwei Zhang, Jingtao Hong, Yuan Tian, David Evans |
| SoK: Unifying Corroborative and Contributive Attributions in Large Language Models | Theodora Worledge, Judy Hanwen Shen, Nicole Meister, Caleb Winston, Carlos Guestrin |
| 2023 | |
| SoK: A Validity Perspective on Evaluating the Justified Use of Data-driven Decision-making Algorithms | Amanda Coston, Anna Kawakami, Haiyi Zhu, Ken Holstein, Hoda Heidari |
| SoK: Harnessing Prior Knowledge for Explainable Machine Learning: An Overview | Katharina Beckh, Sebastian Müller, Matthias Jakobs, Vanessa Toborek, Hanxiao Tan, Raphael Fischer, Pascal Welke, Sebastian Houben, Laura von Rueden |
| SoK: Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks | Tilman Rauker, Anson Ho, Stephen Casper, Dylan Hadfield-Menell |