Multi-LLM systems can produce mathematically incoherent probability distributions; you can detect and repair this using compositional residuals and projection methods, gaining measurable improvements in prediction accuracy.
When multiple LLMs work together to make probabilistic predictions, their individual outputs can violate basic probability rules even if each component is internally consistent. This paper formalizes this problem, shows how to detect it at runtime, and proposes methods to fix the inconsistencies.