Generative modeling has recently gained massive attention given high-profile successes in natural language processing and computer vision. However, there remain major challenges in deploying generative models for real-world impact in domains like healthcare and biology. This is a challenging agenda that requires collaboration across multiple research fields and industry stakeholders. This workshop aims to advance such interdisciplinary conversations around challenges in deploying generative models – the lessons learned by deploying large language models could be impactful for other high stakes domains. Specifically, we will solicit contributions that prioritize (1) Multimodal capabilities in generative modeling, (2) Deployment critical features in generative models such as Safety, Interpretability, Robustness, Ethics, Fairness and Privacy, and (3) Human facing evaluation of generative models.
Tim Salimans
Staff Research Scientist Google Brain
Finale Doshi-Velez
Professor Harvard University
Olga Russakovsky
Assistant Professor Princeton University
Kyunghyun Cho
Associate Professor NYU / Genentech
Deep Ganguli
Research Scientist Anthropic
Pamela Mishkin
Researcher OpenAI
Alan Aspuru-Guzik
Professor University of Toronto
Daphne Ippolito
Assistant Professor Carnegie Mellon University
Swami Sankaranarayanan
Postdoctoral Associate MIT
Thomas Hartvigsen
Postdoctoral Associate MIT
Camille Bilodeau
Assistant Professor University of Virginia
Ryutaro Tanno
Research Scientist Google Deepmind
Cheng Zhang
Principal Researcher Microsoft Research, Cambridge
Florian Tremer
Assistant Professor ETH, Zurich
Phillip Isola
Associate Professor MIT