Yihong Tang

Models can achieve higher accuracy in nuanced football predictions, even when overall match result accuracy shows only slight improvements over traditional baselines.

AWM enables autonomous vehicles to effectively learn from adversarial scenarios, significantly enhancing their robustness in rare and critical traffic conditions.

MobEvolve outperforms traditional methods by evolving its logic through targeted updates, achieving unprecedented fidelity and interpretability in human mobility generation.

RL fine-tuning can make your role-playing agent *worse* at embodying its character, unless you carefully balance task rewards with stylistic constraints.