Ziyi Song — accepted AI-conference papers

2026

UniMM-V2X: MoE-Enhanced Multi-Level Fusion for End-to-End Cooperative Autonomous Driving

Ziyi Song, Chen Xia, Chenbing Wang, Haibao Yu, Sheng Zhou, Zhisheng Niu

AAAI 2026technical

Autonomous driving holds transformative potential but remains fundamentally constrained by the limited perception and isolated decision-making with standalone intelligence. While recent multi-agent approaches introduce cooperation, they often focus merely on perception-level tasks, overlooking the a

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2025

WHALES: A Multi-Agent Scheduling Dataset for Enhanced Cooperation in Autonomous Driving

Yinsong Richard Wang, Siwei Chen, Ziyi Song, Sheng Zhou

IROS 2025

Cooperative perception research is hindered by the limited availability of datasets that capture the complexity of real-world Vehicle-to-Everything (V2X) interactions, particularly under dynamic communication constraints. To address this gap, we introduce WHALES (Wireless enHanced Autonomous vehicle

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