3 papers
cs.CV2026
Non-Forgetting Knowledge Allocation with Bi-level Competition for Class-Incremental Learning
Xiang Tan, Run He, Yawen Cui +6
Class-Incremental Learning (CIL) with pre-trained models (PTMs) aims to sequentially adapt PTMs to new categories without forgetting old knowledge. Built upon PTMs, existing adapte…
cs.LG2025
Analytic Subspace Routing: How Recursive Least Squares Works in Continual Learning of Large Language Model
Kai Tong, Kang Pan, Xiao Zhang +5
Large Language Models (LLMs) possess encompassing capabilities that can process diverse language-related tasks. However, finetuning on LLMs will diminish this general skills and co…
cs.CV2025
Semantic Shift Estimation via Dual-Projection and Classifier Reconstruction for Exemplar-Free Class-Incremental Learning
Run He, Di Fang, Yicheng Xu +5
Exemplar-Free Class-Incremental Learning (EFCIL) aims to sequentially learn from distinct categories without retaining exemplars but easily suffers from catastrophic forgetting of…