Functional Subnetwork Localization for Efficient Continual Learning in Large Language Models
arXiv:2610.21537v1 Announce Type: new Abstract: Biological intelligence continually adapts to new information while retaining prior skills through localized plasticity. In contrast, continual learning in large language models (LLMs) remains vulnerable to catastrophic forgetting. A promising direction is to identify functionally specialized subnetworks within LLMs that enable targeted and resource-efficient adaptation. Using gradient-attribution profiling, we localize cognition-associated functi…