SEF-CLGC at SemEval-2026 Task 11: Logical Notation Impact on Language Model Performance
Hanna Abi Akl, Fabien Gandon, Catherine Faron, Pierre Monnin
cs.CL cs.AI
Abstract
This paper revisits our pipeline called Syllogistic Evaluation Framework-Common Logic Grammar Construction (SEF-CLGC). We combine formal logical notations with Small Language Models (SLMs) to evaluate reasoning performance on the SemEval-2026 Task 11 Subtask 1: Disentangling Content and Formal Reasoning in Large Language Models. Our experiments show that by relying solely on SLMs, trained on a combination of natural and symbolic languages, our best model achieves a content score of 27.80% on the task while significantly lowering the content bias in reasoning.
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Classified with taxonomy v2 on Wed, 2 Sept 2026.