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Found 3 papers, 2 papers with code
LangProp: A code optimization framework using Language Models applied to driving
LangProp is a framework for iteratively optimizing code generated by large language models (LLMs) in a supervised/reinforcement learning setting.
GAIA-1: A Generative World Model for Autonomous Driving
Autonomous driving promises transformative improvements to transportation, but building systems capable of safely navigating the unstructured complexity of real-world scenarios remains challenging.
Model-Based Imitation Learning for Urban Driving
Our approach is the first camera-only method that models static scene, dynamic scene, and ego-behaviour in an urban driving environment.
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