In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI

no code implementations • 21 Mar 2025 • Shayne Longpre, Kevin Klyman, Ruth E. Appel, Sayash Kapoor, Rishi Bommasani, Michelle Sahar, Sean McGregor, Avijit Ghosh, Borhane Blili-Hamelin, Nathan Butters, Alondra Nelson, Amit Elazari, Andrew Sellars, Casey John Ellis, Dane Sherrets, Dawn Song, Harley Geiger, Ilona Cohen, Lauren McIlvenny, Madhulika Srikumar, Mark M. Jaycox, Markus Anderljung, Nadine Farid Johnson, Nicholas Carlini, Nicolas Miailhe, Nik Marda, Peter Henderson, Rebecca S. Portnoff, Rebecca Weiss, Victoria Westerhoff, Yacine Jernite, Rumman Chowdhury, Percy Liang, Arvind Narayanan

The widespread deployment of general-purpose AI (GPAI) systems introduces significant new risks.

Identifying Products in Online Cybercrime Marketplaces: A Dataset for Fine-grained Domain Adaptation

1 code implementation • EMNLP 2017 • Greg Durrett, Jonathan K. Kummerfeld, Taylor Berg-Kirkpatrick, Rebecca S. Portnoff, Sadia Afroz, Damon McCoy, Kirill Levchenko, Vern Paxson

One weakness of machine-learned NLP models is that they typically perform poorly on out-of-domain data.

Domain Adaptation named-entity-recognition +4