NAVSIMv-2

NAVSIMv-2 is a dataset/benchmark used to evaluate the performance of end-to-end autonomous driving systems through collaborative imitation and reinforcement learning.

Papers using NAVSIMv-2 (4)

Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving2026DreamerAD: Efficient Reinforcement Learning via Latent World Model for Autonomous Driving2026WAM-Diff: A Masked Diffusion VLA Framework with MoE and Online Reinforcement Learning for Autonomous Driving2025IRL-VLA: Training an Vision-Language-Action Policy via Reward World Model2025