arXiv Machine Learning August 11, 2026 By Yu Ma, Hongli Shi, Jing Li, Xinran Xu, Weiwei Hou

When Skills Meet Safety: Benchmarking and Characterizing the Adaptive Jailbreak Robustness of Skill-Merged LLMs

Read the original on arXiv Machine Learning →

arXiv:2608. 08542v1 Announce Type: new Abstract: Model merging has become the default way to give an aligned language model new skills without retraining: a practitioner folds task vectors from math, code, or domain specialists into a safety-aligned base using task arithmetic, TIES, or DARE.

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