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Miranda Bogen

2 accepted papers

2025

Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research

NeurIPS 2025oral

"Machine unlearning" is a popular proposed solution for mitigating the existence of content in an AI model that is problematic for legal or moral reasons, including privacy, copyright, safety, and more. For example, unlearning is often invoked as a solution for removing the effects of specific infor…

Cited by 0SourceScholar
2024

Position: On the Societal Impact of Open Foundation Models

ICML 2024oral

Foundation models are powerful technologies: how they are released publicly directly shapes their societal impact. In this position paper, we focus on *open* foundation models, defined here as those with broadly available model weights (e.g., Llama 3, Stable Diffusion XL). We identify five distincti…

Cited by 4SourcePDFScholar