MAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving
Overview
This research presents MAPLE, a novel framework designed to improve the robustness of vision-language-action (VLA) models in end-to-end autonomous driving.
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“l fidelity to the real-world. MAPLE achieves state-of-the-art driving performance on Bench2Drive and demonstrates scalable, closed-loop multi-agent play for robust E2E autonomous driving systems.”
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- arXiv Robotics — research abstractsSignalMAPLE: Latent Multi-Agent Play for End-to-End Autonomous Driving
This research presents MAPLE, a novel framework designed to improve the robustness of vision-language-action (VLA) models in end-to-end autonomous driving.
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