1 code implementation • 9 May 2024 • Shan Chen, Jack Gallifant, Mingye Gao, Pedro Moreira, Nikolaj Munch, Ajay Muthukkumar, Arvind Rajan, Jaya Kolluri, Amelia Fiske, Janna Hastings, Hugo Aerts, Brian Anthony, Leo Anthony Celi, William G. La Cava, Danielle S. Bitterman
Large language models (LLMs) are increasingly essential in processing natural languages, yet their application is frequently compromised by biases and inaccuracies originating in their training data.
no code implementations • 8 May 2024 • Lasse Hyldig Hansen, Nikolaj Andersen, Jack Gallifant, Liam G. McCoy, James K Stone, Nura Izath, Marcela Aguirre-Jerez, Danielle S Bitterman, Judy Gichoya, Leo Anthony Celi
We find widespread disparities in the associations of specific racial and gender terms with the 18 diseases analyzed.
1 code implementation • 28 Mar 2024 • Shan Chen, Jack Gallifant, Marco Guevara, Yanjun Gao, Majid Afshar, Timothy Miller, Dmitriy Dligach, Danielle S. Bitterman
Generative models have been showing potential for producing data in mass.
2 code implementations • 11 Jan 2024 • Matthew B. A. McDermott, Lasse Hyldig Hansen, Haoran Zhang, Giovanni Angelotti, Jack Gallifant
In machine learning (ML), a widespread adage is that the area under the precision-recall curve (AUPRC) is a superior metric for model comparison to the area under the receiver operating characteristic (AUROC) for binary classification tasks with class imbalance.