no code implementations • 26 Oct 2023 • Ahmed Magooda, Alec Helyar, Kyle Jackson, David Sullivan, Chad Atalla, Emily Sheng, Dan Vann, Richard Edgar, Hamid Palangi, Roman Lutz, Hongliang Kong, Vincent Yun, Eslam Kamal, Federico Zarfati, Hanna Wallach, Sarah Bird, Mei Chen
We present a framework for the automated measurement of responsible AI (RAI) metrics for large language models (LLMs) and associated products and services.
1 code implementation • 24 Jan 2019 • Paul Azunre, Craig Corcoran, Numa Dhamani, Jeffrey Gleason, Garrett Honke, David Sullivan, Rebecca Ruppel, Sandeep Verma, Jonathon Morgan
Simulated data containing a set of base classes is first used to learn an initial set of weights.
no code implementations • 4 Apr 2018 • Paul Azunre, Craig Corcoran, David Sullivan, Garrett Honke, Rebecca Ruppel, Sandeep Verma, Jonathon Morgan
This paper describes an abstractive summarization method for tabular data which employs a knowledge base semantic embedding to generate the summary.