13 papers
TwinIR: Coordinated Invisible Dual-Point Attacks on Online HD Map Construction
Haibo Hu, Jianghuai Deng, Chen Tang +3
Online HD map construction is critical to prediction and planning in autonomous driving. We find that existing physical attacks against online map construction are limited by a cro…
Mode-as-Sequence: Translating Multimodal Motion Prediction into Unified Sequential Mode Modeling
Zikang Zhou, Haibo Hu, Xinhong Chen +5
Multimodal motion forecasting is inherently under-supervised: each training scene provides only one realized future, yet multiple plausible futures exist. This sparse supervision o…
DeeAD: Dynamic Early Exit of Vision-Language Action for Efficient Autonomous Driving
Haibo HU, Lianming Huang, Nan Guan +1
Vision-Language Action (VLA) models unify perception, reasoning, and trajectory generation for autonomous driving, but suffer from significant inference latency due to deep transfo…
On-Demand Multi-Task Sparsity for Efficient Large-Model Deployment on Edge Devices
Lianming Huang, Haibo Hu, Qiao Li +2
Sparsity is essential for deploying large models on resource constrained edge platforms. However, optimizing sparsity patterns for individual tasks in isolation ignores the signifi…
MMRHP: A Miniature Mixed-Reality HIL Platform for Auditable Closed-Loop Evaluation
Mingxin Li, Haibo Hu, Jinghuai Deng +3
Validation of autonomous driving systems requires a trade-off between test fidelity, cost, and scalability. While miniaturized hardware-in-the-loop (HIL) platforms have emerged as…
Nav-EE: Navigation-Guided Early Exiting for Efficient Vision-Language Models in Autonomous Driving
Haibo Hu, Lianming Huang, Xinyu Wang +4
Vision-Language Models (VLMs) are increasingly applied in autonomous driving for unified perception and reasoning, but high inference latency hinders real-time deployment. Early-ex…