Tianze Zhu — accepted AI-conference papers

2026

FASIONAD: Adaptive Uncertainty-Gated Fast–Slow Fusion Framework for Safe Autonomous Driving

Ziang Luo, Sicong Jiang, Kangan Qian, Zilin Huang, Tianze Zhu, Siwen Jiao +8

ICRA 2026poster

Previous fast–slow system architectures demonstrated that pairing a reactive E2E planner with a deliberative vision-language model (VLM) can address these long-tail scenarios. However, these dual-system models that query the slow module at fixed intervals are computationally inefficient and introduc…

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2025

AgentThink: A Unified Framework for Tool-Augmented Chain-of-Thought Reasoning in Vision-Language Models for Autonomous Driving

Kangan Qian, Sicong Jiang, Yang Zhong, Ziang Luo, Zilin Huang, Tianze Zhu +16

EMNLP 2025

Vision-Language Models (VLMs) show promise for autonomous driving, yet their struggle with hallucinations, inefficient reasoning, and limited real-world validation hinders accurate perception and robust step-by-step reasoning. To overcome this, we introduce AgentThink , a pioneering unified framewor

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