Are you Talking Logic to Me? Assessing Language Models Syllogistic Reasoning Capabilities
Language models (LMs) struggle with logical tasks like reasoning on syllogisms. It has been shown that Knowledge Representation (KR) plays a crucial role in expressing input information to help models solve tasks. This observation motivates our study of the impact of different formal KR notations on syllogistic reasoning by extending the FOLIO and P-FOLIO datasets. Our experiments on Small Language Models (SLMs) in Supervised Fine-Tuning (SFT) and Zero-Shot (ZS) settings show that the choice of input notation can yield performances competitive with natural language while enabling faster inference. We also propose a syllogistic categorization method (SEF) and use it to enrich ZS prompts wi...
| Authors | Hanna Abi Akl, Fabien Gandon, Catherine Faron et al. |
|---|---|
| Primary category | cs.CL |
| Published | 22 July 2026 |
| Last updated at source | 22 July 2026 |
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