Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control

ArXi:2512.23292v3 Announce Type: replace-cross The prevailing paradigm in AI for physical systems (scaling general-purpose foundation models toward universal multimodal reasoning) confronts a fundamental barrier at the control interface. Recent benchmarks show that even frontier vision--language models achieve only 50--53% accuracy on basic quantitative physics tasks, behaving as approximate guessers that preserve semantic plausibility by violating physical constraints.