Time-Continuous Modeling for Temporal Affective Pattern Recognition in LLMs

摘要

This paper introduces a dataset and conceptual framework for LLMs to mimic real world emotional dynamics through time and in-context learning leveraging physics-informed neural network, opening a possibility for interpretable dialogue modeling.