Author

Zhiling Guo

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Preprint Oct 2026

ASCENT: First-Order Optimal Fine-Tuning with Recalibration for Safety--Utility Co-Enhancement

Supervised fine-tuning can substantially improve the downstream utility of large language models (LLMs) but may compromise their safety. Existing safety-preserving methods constrain downstream updates using safety-related parameters or subspaces, but mainly focus on safety preservation rather than joint safety and util...

Wei-Wei Qi, Chong-Yu Wang, Tian-Hang Zheng et al. · 0 citations

Jul 2026

DARWIN: Evolving Jailbreak Adversary and Guardrail for LLM Safety Evaluation and Protection

DARWIN, an evolutionary attack-defense framework that models jailbreaking as a continual process and updates guardrails through an attack-defense loop is proposed, an evolutionary attack-defense framework that models jailbreaking as a continual process and updates guardrails through an attack-defense loop.

Weiwei Qi, Ze-Feng Wu, Zhiling Guo et al. · arXiv.org · 4 citations