Girmaw Abebe Tadesse, Celia Cintas, et al.
ICML 2020
With widespread adoption of AI models for important decision making, ensuring reliability of such models remains an important challenge. In this paper, we present an end-to-end generic framework for testing AI Models which performs automated test generation for different modalities such as text, tabular, and time-series data and across various properties such as accuracy, fairness, and robustness. Our tool has been used for testing industrial AI models and was very effective to uncover issues present in those models. Demo video link-https://youtu.be/984UCU17YZ.
Girmaw Abebe Tadesse, Celia Cintas, et al.
ICML 2020
Jayaraman J. Thiagarajan, Bindya Venkatesh, et al.
AAAI 2020
Raúl Fernández Díaz, Lam Thanh Hoang, et al.
IRB-AI-DD 2025
Himanshu Gupta, Sameep Mehta, et al.
CLOUD 2017