1 citations · 1 across the 6 of their papers we have counts for
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HMVLM: Multistage Reasoning-Enhanced Vision-Language Model for Long-Tailed Driving Scenarios
Daming Wang, Yuhao Song, Zijian He +4
We present HaoMo Vision-Language Model (HMVLM), an end-to-end driving framework that implements the slow branch of a cognitively inspired fast-slow architecture. A fast controller…
HMAD: Advancing E2E Driving with Anchored Offset Proposals and Simulation-Supervised Multi-target Scoring
Bin Wang, Pingjun Li, Jinkun Liu +7
End-to-end autonomous driving faces persistent challenges in both generating diverse, rule-compliant trajectories and robustly selecting the optimal path from these options via lea…
CogAD: Cognitive-Hierarchy Guided End-to-End Autonomous Driving
Zhennan Wang, Jianing Teng, Canqun Xiang +4
While end-to-end autonomous driving has advanced significantly, prevailing methods remain fundamentally misaligned with human cognitive principles in both perception and planning.…
Quality over Quantity: Boosting Data Efficiency Through Ensembled Multimodal Data Curation
Jinda Xu, Yuhao Song, Daming Wang +4
In an era overwhelmed by vast amounts of data, the effective curation of web-crawl datasets is essential for optimizing model performance. This paper tackles the challenges associa…