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Demonstrates a dual-path engine evaluating physics via language and visual models, highlighting limitations in reasoning.
This paper describes a dual-path implicit physics engine in which the same physical scenario is evaluated through two independent channels: a text physics path (language model) and a visual physics path (diffusion model). The delta between outputs measures where language fails as a proxy for physical reasoning. The architecture was discovered accidentally during implementation of an embodied AI agent.
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Brian Riggleman (2026) studied this question.
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