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A Concept and Argumentation based Interpretable Model in High Risk Domains
Interpretability has become an essential topic for artificial intelligence in some high-risk domains such as healthcare, bank and security.
BTPK-based interpretable method for NER tasks based on Talmudic Public Announcement Logic
In this paper, we propose a novel interpretable method, BTPK (Binary Talmudic Public Announcement Logic model), to help users understand the internal recognition logic of the name entity recognition tasks based on Talmudic Public Announcement Logic.
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