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Lagrange achieves robust open-world driving by transforming decision-making into a Lagrangian action minimization problem, ensuring both interpretability and compliance with vehicle kinematics.
Freezing most of your critic network and only training a tiny LoRA adapter can dramatically improve off-policy RL performance and stability.
