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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Proposes treating Pāṇini's Astādhyāyī as a unifying computational architecture and benchmark foundation for Indic language NLP to improve accuracy, data efficiency, and transfer.
An integrated framework using autoencoders, deep reinforcement learning, and LLMs automates risk-based prioritization and contextual analysis of suspicious network traffic within Splunk SOC environments.
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A P\={a}ninian Foundation for Indic Language Processing
Proposes treating Pāṇini's Astādhyāyī as a unifying computational architecture and benchmark foundation for Indic language NLP to improve accuracy, data efficiency, and transfer.