Austin Zane — accepted AI-conference papers

2025

Evaluation and Incident Prevention in an Enterprise AI Assistant

Akash V. Maharaj, David Arbour, Daniel Lee, Uttaran Bhattacharya, Anup Rao, Austin Zane +3

AAAI 2025technical

Enterprise AI Assistants are increasingly deployed in domains where accuracy is paramount, making each erroneous output a potentially significant incident. This paper presents a comprehensive framework for monitoring, benchmarking, and continuously improving such complex, multi-component systems und…

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2024

Minimum-Norm Interpolation Under Covariate Shift

Neil Rohit Mallinar, Austin Zane, Spencer Frei, Bin Yu

ICML 2024poster

Transfer learning is a critical part of real-world machine learning deployments and has been extensively studied in experimental works with overparameterized neural networks. However, even in the simplest setting of linear regression a notable gap still exists in the theoretical understanding of tra…

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