Author

Ling-Xiang Wang

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#artificial intelligence Preprint Oct 2026

Stability-Plasticity Balance via Singular-Vector Selection in LLM Continual Learning

Domain-specific continual adaptation of LLMs risks catastrophic forgetting, creating a fundamental tension between acquiring new capabilities and preserving those learned during pretraining. PEFT mitigates this problem by restricting the number of trainable parameters, but existing methods lack a principled unit for de...

Ling-Xiang Wang, Hai-Nan Zhang, Liang Pang et al. · 0 citations

#artificial intelligence Nov 2025

Parameter Importance-Driven Continual Learning for Foundation Models

Experiments across three language models and two multimodal models show that PIECE maintains general capabilities and achieves state-of-the-art continual learning performance across diverse downstream tasks, highlighting a practical path to scalable, domain-adaptive foundation models without catastrophic forgetting.

Ling-Xiang Wang, Hai-Nan Zhang, Zhi-Ming Zheng · arXiv.org · 2 citations