Author

Xiangning Lin

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Review Jul 2026

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

A user-centric framework for systematically auditing system prompts in AI systems, AISPA is introduced, a user-centric framework for systematically auditing system prompts in AI systems that examines specific parts of a system prompt and evaluates them along eight dimensions that matter to users.

Xiangning Lin, Shenzhe Zhu, Shu Yang et al. · arXiv.org · 0 citations

Preprint Aug 2026

Towards More Expressive Spoken LLMs: Fine-Grained Intent Benchmarking and Acoustic-Lexical Decoupled Policy Optimization

ParaIntent is introduced, a Chinese benchmark comprising 14 intent categories with balanced explicit and implicit samples, together with a multidimensional evaluation protocol covering intent fulfillment, response quality, and emotional expression, which improves over standard GRPO on most automatic metrics and achieve...

Xiangning Lin, Tian-Hao Zhang, Chunfeng Wang et al. · 1 citation