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Xiaofei Xie

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Open access Oct 2026

Are We Stuck? Modeling and Detecting Deadlocks in Multi-autonomous Vehicle Systems

Autonomous driving system (ADS) testing is essential to ensure the safety and reliability of autonomous vehicles (AVs) prior to deployment. As ADSs are increasingly deployed in multi-AV traffic environments, it becomes crucial to assess their cooperative performance, particularly with respect to deadlock, a fundamental...

Ming-Fei Cheng, Xiao-Fei Xie, Li-Li Quan et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Before Acting, Change the State: Prospective State Intervention for Web Agents under Deceptive Interfaces

Veer is introduced, an agent-side runtime defense that leaves task planning to the base agent and intervenes on Web state when a proposed action would produce an unauthorized consequence, establishing task-relevant Web state as an effective runtime control target for protecting Web agents from deceptive outcomes.

Ruo-Zhao Yang, Ming-Fei Cheng, Xiao-Fei Xie · 0 citations
Jul 2026

EvoEye: Self-Evolving Runtime Monitoring for Autonomous Driving Systems

EvoEye is proposed, which identifies the current monitor's errors, generates informative executions accordingly, and updates the monitor through self-evolution to enable effective self-evolution.

Mingfei Cheng, Lionel C. Briand, Xiaofei Xie · 0 citations
Preprint Jul 2026

Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference

This work proposes FlowFixer, a diagnosis-driven automated repair framework for agentic workflows that first transforms workflow executions into unified symbolic traces and performs symbolic inference to derive executable behavioral specifications that capture node correctness, temporal dependencies, and causal relatio...

Xuyan Ma, Yawen Wang, Junjie Wang et al. · 0 citations
Review Aug 2026

PRWeaver: Evaluating LLM-Based Code Auditors against Long-Horizon Malicious Pull Requests

The results show that access to repository history is insufficient: concealment becomes most effective when benign and malicious changes jointly occupy the auditor's active review context or when the stated purpose plausibly accounts for the attack-bearing diff.

Yuekun Wang, Ming-Fei Cheng, Xiao-Fei Xie · 0 citations

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