From Prediction to Justification: Aligning Sentiment Reasoning with Human Rationale via Reinforcement Learning

arXiv:2604.13398v1 Announce Type: cross Abstract: While Aspect-based Sentiment Analysis (ABSA) systems have achieved high accuracy in identifying sentiment polarities, they often operate as "black boxes," lacking the explicit reasoning capabilities characteristic of human affective cognition. Humans do not merely categorize sentiment; they construct causal explanations for their judgments. To bridge this gap, we propose ABSA-R1, a large language model framework designed to mimic this ``reason-be