2 papers
cs.CV2026
Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training
Hongzhi Ruan, Pei Liu, Weiliang Ma +5
Data scaling is fundamental to modern deep learning, and grows increasingly critical as autonomous driving shifts to end-to-end learning. Real-world driving data is expensive to an…
cs.CV2025
DriveAction: A Benchmark for Exploring Human-like Driving Decisions in VLA Models
Yuhan Hao, Zhengning Li, Lei Sun +7
Vision-Language-Action (VLA) models have advanced autonomous driving, but existing benchmarks still lack scenario diversity, reliable action-level annotation, and evaluation protoc…