Bohao Qu — accepted AI-conference papers

2026

Exploiting Geometric Structures for Modeling Multi-Agent Behaviors: A New Thinking

Bohao Qu, Xiaofeng Cao, Bing Li, Menglin Zhang, Tuan-Anh Vu, Di Lin +1

AAAI 2026technical

In this paper, we rethink model agent behaviors from a geometric structure perspective in multi-agent reinforcement learning. Modeling agent behaviors is essential for understanding how agents interact and facilitating effective decisions. The key lies in capturing the dependencies and sequential re

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2026

Open-Ended Instruction Realization with LLM-Enabled Multi-Planner Scheduling in Autonomous Vehicles

Jiawei Liu, Xun Gong, Fen Fang, Muli Yang, Bohao Qu, Yunfeng Hu +3

CVPR 2026

Most Human-Machine Interaction (HMI) research overlooks the maneuvering needs of passengers in autonomous driving (AD). Natural language offers an intuitive interface, yet translating passenger open-ended instructions into control signals--without sacrificing interpretability and traceability--remai

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