18 citations · 49 across the 10 of their papers we have counts for
5 papers · 1 filter
SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training
Gengwei Zhang, Liyuan Wang, Guoliang Kang +2
In recent years, continual learning with pre-training (CLPT) has received widespread interest, instead of its traditional focus of training from scratch. The use of strong pre-trai…
HiDe-PET: Continual Learning via Hierarchical Decomposition of Parameter-Efficient Tuning
Liyuan Wang, Jingyi Xie, Xingxing Zhang +2
The deployment of pre-trained models (PTMs) has greatly advanced the field of continual learning (CL), enabling positive knowledge transfer and resilience to catastrophic forgettin…
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction Alignment
Kanglei Zhou, Junlin Li, Ruizhi Cai +3
Action Quality Assessment (AQA) is pivotal for quantifying actions across domains like sports and medical care. Existing methods often rely on pre-trained backbones from large-scal…
Orchestrate Latent Expertise: Advancing Online Continual Learning with Multi-Level Supervision and Reverse Self-Distillation
HongWei Yan, Liyuan Wang, Kaisheng Ma +1
To accommodate real-world dynamics, artificial intelligence systems need to cope with sequentially arriving content in an online manner. Beyond regular Continual Learning (CL) atte…
MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment
Kanglei Zhou, Liyuan Wang, Xingxing Zhang +4
Action Quality Assessment (AQA) evaluates diverse skills but models struggle with non-stationary data. We propose Continual AQA (CAQA) to refine models using sparse new data. Featu…