Author

Jia-Yang Li

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Open access 2026

PAIR: Against Inference-Time Attacks on Fine-Tuned LLMs via Path-Level Inference Randomization

PAIR, a dynamic framework that applies path-level randomization within LoRA adapters during inference, indicates that inference-time randomization at the path level can strengthen fine-tuned LLMs against the evaluated security and privacy attacks.

Jia-Yang Li, Tian-Qing Zhu, Da-Yong Ye et al. · IEEE Transactions on Informa... · 0 citations

#artificial intelligence Preprint Oct 2026

Hidden Risks of Jev: An Empirical Study of Security, Privacy, and Dual Use

Jev turns natural-language questions into typed answers and probabilities with low latency and cost, enabling applications to route requests and select tools. While this interface allows Jev to integrate naturally into application workflows as a decision layer, the security and privacy implications of this emerging use...

Shang Wang, Tian-Qing Zhu, Hua-Jie Chen et al. · 1 citation