This paper reconstructs Toegye Yi Hwang's philosophy into a five-stage EEFS architecture with design principles, scenario classifications, and an evaluation instrument for ethical emotion regulation in agentic AI.
In: 2025 IEEE International Conference on Electro Information Technology (eIT)
4 Pith papers cite this work, alongside 6 external citations. Polarity classification is still indexing.
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2026 4roles
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Proposes treating Pāṇini's Astādhyāyī as a unifying computational architecture and benchmark foundation for Indic language NLP to improve accuracy, data efficiency, and transfer.
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A systematic review of 21 peer-reviewed papers identifies two classification approaches for agentic AI governance (autonomous goal-pursuit and moral agency), synthesizes privacy concerns, and evaluates Singapore's Model AI Governance Framework as the first dedicated agentic AI governance model.
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Designing Ethical Learning for Agentic AI: Toegye Yi Hwang's Ethical Emotion Regulation Framework
This paper reconstructs Toegye Yi Hwang's philosophy into a five-stage EEFS architecture with design principles, scenario classifications, and an evaluation instrument for ethical emotion regulation in agentic AI.
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