馃敩 Research Summary by Caner Hazirbas, Research Scientist at Meta and Ph.D. graduate in Computer Vision from the Technical University of Munich. [Original paper by Caner Hazirbas, Alicia Sun, Yonathan Efroni, Mark … [Read more...] about The Bias of Harmful Label Associations in Vision-Language Models
Design
Self-Improving Diffusion Models with Synthetic Data
馃敩 Research Summary by Sina Alemohammad, a PhD candidate at Rice University with a focus on the interaction between generative models and synthetic data. [Original paper by Sina Alemohammad, Ahmed Imtiaz Humayun, … [Read more...] about Self-Improving Diffusion Models with Synthetic Data
The Montreal AI Ethics Institute (MAIEI) Joins the AI Alliance
The Montreal AI Ethics Institute (MAIEI) is delighted to announce its membership in the AI Alliance. This collaborative venture kicked off with an event in Toronto on June 17, co-hosted with IBM, Meta and ServiceNow to … [Read more...] about The Montreal AI Ethics Institute (MAIEI) Joins the AI Alliance
The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice
馃敩 Research Summary by聽Stephen Yang and Fernando Delgado. Stephen Yang is a PhD student at the University of Southern California studying how careful human intervention is possible at the speed and scale of AI. … [Read more...] about The Participatory Turn in AI Design: Theoretical Foundations and the Current State of Practice
Responsible Generative AI: A Reference Architecture for Designing Foundation Model-based Agents
馃敩 Research Summary by Dr. Qinghua Lu, the team leader of the Responsible AI science team at CSIRO's Data61 and is the winner of the 2023 APAC Women in AI Trailblazer Award. [Original paper by Qinghua Lu, Liming … [Read more...] about Responsible Generative AI: A Reference Architecture for Designing Foundation Model-based Agents