Dharshan Kumaran

Abstract Large language models (LLMs) are increasingly deployed in high-stakes applications where reliable confidence estimation is crucial for trustworthy artificial intelligence (AI). However, their confidence dynamics remain poorly understood, with users reporting paradoxical behaviours: LLMs exhibit reduced flexibility in updating initial responses while simultaneously showing excessive sensitivity to contradictory feedback.

Neural Activity in the Amygdala and Anterior Hippocampus Correlates with SMC-Modeled Difference between the Power of Individuals during Test Trials Hierarchy Updating: The SMC Model Provides a Superior Fit to Neural Data Compared with the RL Model Activity in the MPFC Correlates with SMC-Modeled Hierarchy Update Signal in the Self Condition during Training Trials Selective Coupling between MPFC and Amygdala and Hippocampal Activity during Updating of Hierarchy Knowledge in the Self Condition...