A neuro-symbolic system using LLM disagreement to trigger Z3 formal verification achieves 94.3% accuracy and a combined score of 41.88 on syllogistic validity prediction, improving on the pure ensemble by reducing content effects.
VERAFI : Verified Agentic Financial Intelligence through Neurosymbolic Policy Generation
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FregeLogic at SemEval 2026 Task 11: A Hybrid Neuro-Symbolic Architecture for Content-Robust Syllogistic Validity Prediction
A neuro-symbolic system using LLM disagreement to trigger Z3 formal verification achieves 94.3% accuracy and a combined score of 41.88 on syllogistic validity prediction, improving on the pure ensemble by reducing content effects.