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20232026
most citedHierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality

18 citations · 22 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.LG2026

Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection

Guanglong Sun, Siyuan Zhang, Liyuan Wang +3

Safety post-training can improve the harmfulness and policy compliance of Large Language Models (LLMs), but it may also reduce general utility, a phenomenon often described as the…

cs.LG2025

Versatile Cardiovascular Signal Generation with a Unified Diffusion Transformer

Zehua Chen, Yuyang Miao, Liyuan Wang +3

Cardiovascular signals such as photoplethysmography (PPG), electrocardiography (ECG), and blood pressure (BP) are inherently correlated and complementary, together reflecting the h…

cs.LG2024

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…

cs.LG2023★ 3 cited

Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation

Yilin Lyu, Liyuan Wang, Xingxing Zhang +4

Continual learning entails learning a sequence of tasks and balancing their knowledge appropriately. With limited access to old training samples, much of the current work in deep n…

cs.LG2023★ 18 cited

Hierarchical Decomposition of Prompt-Based Continual Learning: Rethinking Obscured Sub-optimality

Liyuan Wang, Jingyi Xie, Xingxing Zhang +3

Prompt-based continual learning is an emerging direction in leveraging pre-trained knowledge for downstream continual learning, and has almost reached the performance pinnacle unde…

cs.LG2023★ 1 cited

Towards a General Framework for Continual Learning with Pre-training

Liyuan Wang, Jingyi Xie, Xingxing Zhang +2

In this work, we present a general framework for continual learning of sequentially arrived tasks with the use of pre-training, which has emerged as a promising direction for artif…