3 papers
cs.LG2026
Sparsity, Superposition, and Forgetting: A Mechanistic Study of Representation Retention in Continual Learning
Jan Wasilewski, Jędrzej Kozal, Michał Woźniak +1
Continual learning (CL) systems often forget previously acquired knowledge, yet the mechanisms driving forgetting remain hard to isolate in practice because real datasets entangle…
cs.LG2026
Unlearning-based sliding window for continual learning under concept drift
Michal Wozniak, Marek Klonowski, Maciej Maczynski +1
Traditional machine learning assumes a stationary data distribution, yet many real-world applications operate on nonstationary streams in which the underlying concept evolves over…
cs.LG2025
Holistic Continual Learning under Concept Drift with Adaptive Memory Realignment
Alif Ashrafee, Jedrzej Kozal, Michal Wozniak +1
Traditional continual learning methods prioritize knowledge retention and focus primarily on mitigating catastrophic forgetting, implicitly assuming that the data distribution of p…