Metacognition—knowing what you know and don't know—is critical for building trustworthy AI systems, and this survey shows practical ways to measure, improve, and apply these abilities in language models.
This paper surveys metacognition in large language models—the ability to monitor and reflect on one's own thinking. It reviews methods to measure metacognitive abilities, techniques to improve them, and applications to make AI systems more reliable and transparent. The work provides the first comprehensive overview of this emerging research area.