Csaba Szepesvári

This paper examines methods to enhance value estimation in reinforcement learning despite challenges.

A new method enhances FQI by using log-loss for improved learning efficiency.

Addressing hallucinations to enhance the reliability of language models.

A look at uncertainty types and their importance in language models.

CMDPs merge reward maximization with safety in AI applications.