4 papers
GeoWAM: Visual Geometry World Action Models for Autonomous Driving
Yiren Lu, Xin Ye, Jiaming Liu +10
World action models (WAMs) have recently gained increasing attention as a framework for jointly modeling scene evolution and ego actions in autonomous driving. Most existing WAMs l…
TraVEL: Trajectory-Guided Video Embedding Learning for Driving-Video Retrieval
Yi-Chung Chen, Philip Jacobson, Tom Lampo +6
Efficiently retrieving relevant clips from large-scale driving logs is essential for data curation, model development, and safety analysis. Structured and rule-based retrieval syst…
VLADriveBench: Evaluating CoT-Action Relationship in VLA for Autonomous Driving
Thach Nguyen, Danhua Guo, Tom Lampo +2
Vision-language-action (VLA) models generate chain-of-thought (CoT) reasoning alongside driving trajectories, but existing benchmarks evaluate only trajectory quality and do not as…
VLGA: Vision-Language-Geometry-Action Models for Autonomous Driving
Jin Yao, Dhruva Dixith Kurra, Tom Lampo +3
Vision-language-action (VLA) models can describe scenes and reason about them in language, yet still struggle to ground their actions in the dense 3D world around them. Existing ap…