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NeSyCat: A Monad-Based Categorical Semantics of the Neurosymbolic ULLER Framework

A paper proposing a monad-based categorical semantics for the Neurosymbolic ULLER framework.

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NeSyCat: A Monad-Based Categorical Semantics of the Neurosymbolic ULLER Framework

arXiv
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The authors present NeSyCat, a monad-based categorical semantics for the Neurosymbolic ULLER framework. This work aims to provide a formal foundation for the framework's neurosymbolic integration.

The proposed semantics is based on category theory and monads, enabling a more rigorous understanding of the framework's behavior.

Abstract

The authors present NeSyCat, a monad-based categorical semantics for the Neurosymbolic ULLER framework. This work aims to provide a formal foundation for the framework's neurosymbolic integration. The proposed semantics is based on category theory and monads, enabling a more rigorous understanding of the framework's behavior.

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neurosymbolicullermonad-basedcategorical-semanticsKnowledge GraphsAI AgentsLarge Language ModelsSemantic Interoperability
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