Project lead, main contributor, correspondence to alexandre.rame@isir.upmc.fr. Equal experimental contribution, order determined at random. Further information and resources related to this project can be found on this website.

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

Evaluating large language models (LLMs) is challenging.

That is, we propose to formulate continual learning as a sequence modeling problem, allowing advanced sequence models to be utilized for continual learning.

These counts have very high global sensitivity.

We consider two versions: sequential, where Bob observes Alice's cut