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The Hong Kong Polytechnic University
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AWM enables autonomous vehicles to effectively learn from adversarial scenarios, significantly enhancing their robustness in rare and critical traffic conditions.
User feedback prediction can be learned, revealing critical performance gaps in AI assistants that traditional evaluation methods overlook.
MobEvolve outperforms traditional methods by evolving its logic through targeted updates, achieving unprecedented fidelity and interpretability in human mobility generation.
Speech-based depression detection isn't just accurate across languages; it's also neurally plausible, aligning with established EEG markers of emotional dysregulation.