LCA: Local Classifier Alignment for Continual Learning

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When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers
2025Hongkang Li, Yihua Zhang et al.
[2]
Boosting Multiple Views for pretrained-based Continual Learning
2025Quyen Tran, T. Tran et al.
[3]
MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
2024Hai-Long Sun, Da-Wei Zhou et al.
[4]
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2023Hai-Long Sun, Da-Wei Zhou et al.
[8]
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2023Prateek Yadav, Derek Tam et al.
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2023Da-Wei Zhou, Han-Jia Ye et al.
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SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model
2023Gengwei Zhang, Liyuan Wang et al.
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Founder's Pitch

"LCA introduces a novel loss function to enhance classifier alignment in continual learning, mitigating catastrophic forgetting."

Continual LearningScore: 7View PDF ↗

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