Author

Chaochao Lu

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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

Preprint Aug 2026

Gradient Immunity: Null-Space Resistance to Malicious Fine-Tuning

A Unidirectional Safety Gate (USG) is proposed, instantiated as a Null Space Cubic Layer together with an Inverse Adapter inserted after the final Transformer layer, suggesting that release-time representation-space blocking can raise the cost of malicious downstream adaptation without requiring downstream cooperation.

Yuxuan Huang, Xingyu Zeng, Tian-Hang Zheng et al. · 0 citations

Preprint Jul 2026

DataShield: Uncovering Risky Fine-Tuning Data Across LLMs Through Consensus Subspace Alignment

DataShield is a data assessment framework that identifies risky fine-tuning samples and response segments through consensus subspace alignment over joint safety-critical semantic spaces derived from multiple safety-aligned LLMs, allowing both sample-level filtering and fine-grained segment-level masking.

Ze-Feng Wu, Weiwei Qi, Jielong Chen et al. · 4 citations