2 citations · 4 across the 7 of their papers we have counts for
3 papers · 1 filter
Paying Alignment Tax with Contrastive Learning
Buse Sibel Korkmaz, Rahul Nair, Elizabeth M. Daly +1
Current debiasing approaches often result a degradation in model capabilities such as factual accuracy and knowledge retention. Through systematic evaluation across multiple benchm…
AI Risk Atlas: Taxonomy and Tooling for Navigating AI Risks and Resources
Frank Bagehorn, Kristina Brimijoin, Elizabeth M. Daly +17
The rapid evolution of generative AI has expanded the breadth of risks associated with AI systems. While various taxonomies and frameworks exist to classify these risks, the lack o…
Foundation Models at Work: Fine-Tuning for Fairness in Algorithmic Hiring
Buse Sibel Korkmaz, Rahul Nair, Elizabeth M. Daly +3
Foundation models require fine-tuning to ensure their generative outputs align with intended results for specific tasks. Automating this fine-tuning process is challenging, as it t…