arXiv AI June 17, 2026 By Vaggelis Dorovatas, Malte Schwerin, Andrew D. Bagdanov, Lucas Caccia, Antonio Carta, Laurent Charlin, Barbara Hammer, Tyler L. Hayes, Timm Hess, Christopher Kanan, Dhireesha Kudithipudi, Xialei Liu, Vincenzo Lomonaco, Jorge Mendez-Mendez, Darshan Patil, Ameya Prabhu, Elisa Ricci, Tinne Tuytelaars, Gido M. van de Ven, Liyuan Wang, Joost van de Weijer, Jonghyun Choi, Martin Mundt, Rahaf Aljundi

Position: Modular Memory is the Key to Continual Learning Agents

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arXiv:2603. 01761v2 Announce Type: replace-cross Abstract: Foundation models have transformed machine learning through large-scale pretraining and increased test-time compute.

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When Does Continual Learning Require Learning

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arXiv Machine Learning

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The Art of Not Forgetting A Local Learning Architecture for Continual Learning

We introduce CMP (Cognitive Memory Primitive), a continual-learning architecture that repre? sents inputs as sparse relational codes, stores them in a two-tier competitive memory, and learns through local updates without end-to-end backpropagation through its feature-generating system.

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