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The Hong Kong Polytechnic University
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MobEvolve outperforms traditional methods by evolving its logic through targeted updates, achieving unprecedented fidelity and interpretability in human mobility generation.
By framing adversarial training as a zero-sum Markov game, ADV-0 finds more diverse safety-critical failures in autonomous driving systems, leading to significantly improved generalization against unseen long-tail risks.
