A Dual-Path Implicit Physics Engine: Measuring the Boundary Where Language Fails
Abstract
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.
Fields of Study & Subjects
Multimodal Machine Learning Applications
Model Reduction and Neural Networks
Artificial Intelligence Applications
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 March 2026
- Language
- EN
- Document type
- Preprint