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cs.AI updates on arXiv.org

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Grounded Inference: Principles for Deterministically Enca...
[Submitted on 18 Jun 2026] · 2026-06-19 · via cs.AI updates on arXiv.org

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Abstract:The incorporation of generative models into traditional computational systems presents both enormous opportunity and tremendous peril. Although many early adopters have realized these perils at great expense, the field still requires foundational frameworks to de-risk incorporation of AI into traditional systems. This manuscript establishes this foundation through the definition of four specific primitives of AI blended architecture, designed to enable deterministic encapsulation of probabilistic models. It further establishes two overarching anti-patterns broadly represented across industry to serve as warnings for engineers in this field. This framework was designed to enable successful integration of AI into traditional systems while providing a foundation upon which generative model providers could build the next generation of generative model interfaces.

Submission history

From: Martin O'Neill [view email]
[v1] Thu, 18 Jun 2026 03:32:19 UTC (196 KB)