A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications

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.

GPT-4

Impact of Label Types on Training SWIN Models with Overhead Imagery

no code implementations • 11 Oct 2023 • Ryan Ford, Kenneth Hutchison, Nicholas Felts, Benjamin Cheng, Jesse Lew, Kyle Jackson

We found that the models trained on only target pixels do not show performance improvement for classification tasks, appearing to conflate background pixels in the evaluation set with target pixels.

Object object-detection +3