565 citations · 702 across the 11 of their papers we have counts for
4 papers · 1 filter
Finetuning Text-to-Image Diffusion Models for Fairness
Xudong Shen, Chao Du, Tianyu Pang +3
The rapid adoption of text-to-image diffusion models in society underscores an urgent need to address their biases. Without interventions, these biases could propagate a skewed wor…
AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI
Ayse Gizem Yasar, Andrew Chong, Evan Dong +9
As AI technology advances rapidly, concerns over the risks of bigness in digital markets are also growing. The EU's Digital Markets Act (DMA) aims to address these risks. Still, th…
Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities
Xudong Shen, Hannah Brown, Jiashu Tao +5
There is increasing attention being given to how to regulate AI systems. As governing bodies grapple with what values to encapsulate into regulation, we consider the technical half…
Inverse Scaling: When Bigger Isn't Better
Ian R. McKenzie, Alexander Lyzhov, Michael Pieler +24
Work on scaling laws has found that large language models (LMs) show predictable improvements to overall loss with increased scale (model size, training data, and compute). Here, w…