Private Adaptations of Large Language Models
Investigating privacy concerns in LLM in-context learning, this talk introduces methods for privately adapting and training large language models to mitigate membership inference attacks.
Self-contained public lectures, keynote addresses, and research seminars.
Investigating privacy concerns in LLM in-context learning, this talk introduces methods for privately adapting and training large language models to mitigate membership inference attacks.