Hind, Michael

3 publications

NeurIPS 2025 BenchmarkCards: Standardized Documentation for Large Language Model Benchmarks Anna Sokol, Elizabeth M. Daly, Michael Hind, David Piorkowski, Xiangliang Zhang, Nuno Moniz, Nitesh V Chawla
AAAI 2022 AI Explainability 360: Impact and Design Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
MLOSS 2020 AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilović, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang