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From the 1 of 7 linked papers with an AI index.

collaborators

7 papers

cs.AI2026

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

Xiangning Lin, Shenzhe Zhu, Shu Yang +23

The paper presents AISPA, a user‑centric framework for auditing the system prompts that guide large language model behavior in commercial AI products, and reports findings from ana…

cs.CL2026

Humanly: A Configurable and Traceable Environment for Human-AI Collaborative Writing

Shenzhe Zhu, Haoqian Zhang, Xu Yang +7

Teachers, conference chairs, and public readers all judge writing from limited evidence, seeing only a finished document and not the process that produced it. Final text alone cann…

cs.LG2026

DOG-DPO:Dynamic Optimization in Geometry for Safety Alignment

Yi Nian, Tiankai Yang, Yudi Zhang +7

Safety alignment for large language models relies on preference data, but current pipelines often train on large, redundant datasets. Existing data selection methods typically scor…

cs.AI2026

When Only the Final Text Survives: Implicit Execution Tracing for Multi-Agent Auditing

Yi Nian, Haosen Cao, Shenzhe Zhu +4

When a multi-agent system produces an incorrect or harmful answer, who is accountable if execution logs and agent identifiers are unavailable? In practice, generated content is oft…

cs.CV2026

AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving

Shuo Xing, Hongyuan Hua, Xiangbo Gao +10

Recent advancements in large vision language models (VLMs) tailored for autonomous driving (AD) have shown strong scene understanding and reasoning capabilities, making them undeni…

cs.AI2025

The Automated but Risky Game: Modeling and Benchmarking Agent-to-Agent Negotiations and Transactions in Consumer Markets

Shenzhe Zhu, Jiao Sun, Yi Nian +3

AI agents are increasingly used in consumer-facing applications to assist with tasks such as product search, negotiation, and transaction execution. In this paper, we explore a fut…