Update README.md

README.md

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 Official CARLA dataset accompanies our paper LEAD: Minimizing Learner–Expert Asymmetry in End-to-End Driving.
 
-> 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:
+> We release the complete pipeline 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:
 > 
 > - Extensive visualization suite and runtime type validation for easier debugging.
 > - Optimized storage format, packs 72 hours of driving in ~200GB.
-> - 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
+> - Native support for NAVSIM and Waymo Vision-based E2E and extending those benchmarks through closed-loop simulation and synthetic data for additional supervision during training.
 
 Find more information on [https://github.com/autonomousvision/lead](https://github.com/autonomousvision/lead).