2026-07-21T15:08:04Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:25412 2026-06-23T08:02:15Z ddc:004 open_access

Deep Continual Learning in the Foundation Model Era (Dagstuhl Seminar 25432) Kanan, Christopher Mundt, Martin Tuytelaars, Tinne van de Weijer, Joost Hess, Timm Felix continual learning deep learning foundation models This report documents the program and the outcomes of Dagstuhl Seminar 25432 "Deep Continual Learning in the Foundation Model Era". This seminar brought together 23 researchers to discuss research at the intersection of continual learning and foundation models. The discussion centered on the major challenges arising from continual training of foundation models, including the need for new benchmarks, new opportunities for memory-based continual learning, emerging application domains, and the development of efficient metrics to quantify forgetting of foundation model knowledge. In addition, the report contains a summery of the talks of the partipants. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Christopher Kanan and Martin Mundt and Tinne Tuytelaars and Joost van de Weijer and Timm Felix Hess 2026 Is Part Of Dagstuhl Reports, Volume 15, Issue 10 (2026) Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagRep.15.10.119 urn:nbn:de:0030-drops-254123 https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.10.119 eng https://creativecommons.org/licenses/by/4.0/legalcode