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#machine learning Preprint Oct 2026

Fine-Grained Analysis of Catastrophic Forgetting in Continual Learning via Algorithmic Stability

Understanding catastrophic forgetting, in which learning new tasks degrades performance on previously learned tasks, remains a fundamental challenge in continual learning (CL). Existing theoretical analyses often rely on specific model or task structures and offer limited insight into how iterative optimization affects...

Guo-Dong Zheng, Y. Sun, Peng Wang et al. · 0 citations
Open access Sep 2026

TeZO: Empowering the Low-Rankness on the Temporal Dimension in the Zeroth-Order Optimization for Fine-Tuning LLMs.

Zeroth-order optimization (ZO) has demonstrated remarkable promise in efficient fine-tuning tasks for Large Language Models (LLMs). In particular, recent advances incorporate the low-rankness of gradients, introducing low-rank ZO estimators to further reduce GPU memory consumption. However, most existing works focus so...

Y. Sun, Qi-Xin Zhang, Liang Ding et al. · 11 citations · ⚡1

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