@inproceedings{akl-etal-2026-sef,
    title = "{SEF}-{CLGC} at {S}em{E}val-2026 Task 11: Logical Notation Impact on Language Model Performance",
    author = "Akl, Hanna Abi  and
      Gandon, Fabien  and
      Faron, Catherine  and
      Monnin, Pierre",
    editor = "Kochmar, Ekaterina  and
      Ghosh, Debanjan  and
      North, Kai  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.semeval-1.285/",
    pages = "2251--2261",
    ISBN = "979-8-89176-414-9",
    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."
}