Emergent Symbolic Structures in Artificial Neural Networks

This paper proposes that artificial neural networks implicitly encode symbolic structures despite their continuous vector representations. The study demonstrates that neural network behavior can be approximated with symbolic formulations and modified through targeted interventions on internal representations.

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