Xin Guo

Even state-of-the-art language models struggle significantly in real-world tasks, exposing critical shortcomings in their deployment readiness.

Time-inconsistent control problems can be tackled effectively with a novel two-stage reinforcement learning algorithm that learns equilibrium policies, bridging theory and practical applications in finance.