arXiv cs.CL
· Papers
Beyond Static Models: An Evolving Framework for Continual Learning in Large Language Models across Training Stages
arXiv:2603.12658v2 Announce Type: replace Abstract: Continual learning (CL) has emerged as a pivotal paradigm to enable large language models (LLMs) to dynamically adapt to evolving knowledge and sequential tasks while mitigating catastrophic forgetting, a critical limitation of the static pre-training paradigm inheren