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

18 citations · 21 across the 5 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.LG20233 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.LG202318 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

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…