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Neuro-symbolic AI studies classified under 'Implicit Intermediate Representations and Implicit Decision Making' utilize neural networks to extract features from data, but these features require an intermediate representation, such as latent vector embeddings or partially explicit structures, to be processed by symbolic logic.

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