Selective Forgetting in LLMs
Executive Summary This work approaches the problem of selectively forgetting knowledge from a large language model (LLM) for the purposes of safety, copyright, security, or otherwise. Also known as machine unlearning, this entails training a model to forget certain elements of the dataset on which it was trained. Unlea...
Jack Dymond, Phil Swatton, Jack Roberts et al.
· Alan Turing Institute Resear... · 0 citations