2024-2026 Japan Society for the Promotion of Science, Grant-in- Aid for Transformative Research Areas (A), Unified Theory, JSPS

Surprisal theory quantifies sentence processing load by the probability of occurrence of words relative to context, allowing comparison of large language models and human sentence processing. This project compares the prediction accuracy of surprisal theory with other methods and examines methods that better explain the relationship between large language models and the human brain.