AI RESEARCH
Patching LLM Like Software: A Lightweight Method for Improving Safety Policy in Large Language Models
arXiv CS.AI
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ArXi:2511.08484v2 Announce Type: replace We propose patching for large language models (LLMs) like software versions, a lightweight and modular approach for addressing safety vulnerabilities. While vendors release improved LLM versions, major releases are costly, infrequent, and difficult to tailor to customer needs, leaving released models with known safety gaps. Unlike full-model fine-tuning or major version updates, our method enables rapid remediation by prepending a compact, learnable prefix to an existing model. This "patch.