New Horizon
Research on "horizon" in various scientific domains focuses on extending the temporal or informational reach of models and algorithms. Current efforts concentrate on developing horizon-free methods in reinforcement learning, improving anomaly detection by incorporating temporal dynamics and context, and evaluating the limitations of models (like Vision-Language Models) when dealing with uncommon data. These advancements are significant for improving the efficiency and robustness of AI systems across diverse applications, from robotics and traffic safety to healthcare and resource management.
Papers
December 30, 2022
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December 12, 2021