Austin Hoag

According to our database, Austin Hoag authored at least 7 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Yes, But Not Always. Generative AI Needs Nuanced Opt-in.

Wiebke Hutiri, Morgan Klaus Scheuerman, Shruti Nagpal, Austin Hoag, Alice Xiang

CoRR, April, 2026

2025

Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference.

Yuhong Luo, Austin Hoag, Xintong Wang, Philip S. Thomas, Przemyslaw A. Grabowicz

CoRR, October, 2025

Reinforcement Learning from Human Feedback with High-Confidence Safety Constraints.

Yaswanth Chittepu, Blossom Metevier, Will Schwarzer, Austin Hoag, Scott Niekum, Philip S. Thomas

CoRR, June, 2025

Fair human-centric image dataset for ethical AI benchmarking.

Alice Xiang, Jerone T. A. Andrews, Rebecca Bourke, William Thong, Julienne LaChance, Tiffany Georgievski, Apostolos Modas, Aida Rahmattalabbi, Yunhao Ba, Shruti Nagpal, Orestis Papakyriakopoulos, Dora Zhao, Jinru Xue, Victoria Matthews, Linxia Gong, Austin Hoag, Mircea Cimpoi, Swami Sankaranarayanan, Wiebke Hutiri, Morgan Klaus Scheuerman, Albert S. Abedi, Peter Stone, Peter R. Wurman, Hiroaki Kitano, Michael Spranger

Nat., 2025

2024

Analyzing the Relationship Between Difference and Ratio-Based Fairness Metrics.

Min-Hsuan Yeh, Blossom Metevier, Austin Hoag, Philip S. Thomas

Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023

Learning Fair Representations with High-Confidence Guarantees.

Yuhong Luo, Austin Hoag, Philip S. Thomas

CoRR, 2023

Seldonian Toolkit: Building Software with Safe and Fair Machine Learning.

Austin Hoag, James E. Kostas, Bruno Castro da Silva, Philip S. Thomas, Yuriy Brun

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: ICSE 2023 Companion Proceedings, 2023