In everyday conversations, humans can take on different roles and adapt their vocabulary to their chosen roles. We explore whether LLMs can take on, that is impersonate, different roles when they generate text in-context.

When deploying machine learning solutions, they must satisfy multiple requirementsbeyondaccuracy,suchasfairness,robustness,orsafety.

Transformers learn to approximate second-order optimization methods for ICL.

Learning the intents of an agent, defined by its goals or motion style, is often extremely challenging from just a few examples.

Machine unlearning is a promising solution for efficiently removing specific knowledge by post hoc modifying models.