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  # Latent TransFuser v6 (NAVSIM)
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- We release the complete pipeline (covering scenario descriptions, expert driver, data preprocessing scripts, training code, and evaluation infrastructure) required to achieve **state-of-the-art closed-loop performance on the Bench2Drive** benchmark. Built around the CARLA simulator, the stack features a data-centric design with:
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- - Extensive visualization suite and runtime type validation for easier debugging.
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- - Optimized storage format, packs 72 hours of driving in ~200GB.
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- - Native support for NAVSIM and Waymo Vision-based E2E, with LEAD extending these benchmarks through closed-loop simulation and synthetic data for additional supervision during training
 
 
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  Find more information on [https://github.com/autonomousvision/lead](https://github.com/autonomousvision/lead).
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  # Latent TransFuser v6 (NAVSIM)
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+ Official model weights for **Latent TransFuser v6 (TFv6)**, a NAVSIM checkpoint accompanies our paper LEAD: Minimizing Learner–Expert Asymmetry in End-to-End Driving.
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+ > We release the complete pipeline (covering scenario descriptions, expert driver, data preprocessing scripts, training code, and evaluation infrastructure) required to achieve **state-of-the-art closed-loop performance on the Bench2Drive** benchmark. Built around the CARLA simulator, the stack features a data-centric design with:
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+ >
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+ > - Extensive visualization suite and runtime type validation for easier debugging.
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+ > - Optimized storage format, packs 72 hours of driving in ~200GB.
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+ > - Native support for NAVSIM and Waymo Vision-based E2E, with LEAD extending these benchmarks through closed-loop simulation and synthetic data for additional supervision during training
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  Find more information on [https://github.com/autonomousvision/lead](https://github.com/autonomousvision/lead).
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