Rank-O-ToM: Unlocking Emotional Nuance Ranking to Enhance Affective Theory-of-Mind

• URL: http://arxiv.org/abs/2503.16461v1
• Date: Mon, 24 Feb 2025 05:04:40 GMT
• Title: Rank-O-ToM: Unlocking Emotional Nuance Ranking to Enhance Affective Theory-of-Mind
• Authors: JiHyun Kim, JuneHyoung Kwon, MiHyeon Kim, Eunju Lee, YoungBin Kim,
• Abstract summary: Ranking the Emotional Nuance for Theory of Mind (Rank-O-ToM) is a framework that leverages ordinal ranking to align confidence levels with the emotional spectrum.<n>Rank-O-ToM enhances the nuanced understanding of emotions, advancing AI's ability to reason about affective states.
• Score: 7.098576908286076
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Facial Expression Recognition (FER) plays a foundational role in enabling AI systems to interpret emotional nuances, a critical aspect of affective Theory of Mind (ToM). However, existing models often struggle with poor calibration and a limited capacity to capture emotional intensity and complexity. To address this, we propose Ranking the Emotional Nuance for Theory of Mind (Rank-O-ToM), a framework that leverages ordinal ranking to align confidence levels with the emotional spectrum. By incorporating synthetic samples reflecting diverse affective complexities, Rank-O-ToM enhances the nuanced understanding of emotions, advancing AI's ability to reason about affective states.

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