arXiv:2607. 23513v1 Announce Type: cross Abstract: Diagrams are widely used to support logical reasoning, and prior studies suggest that representations such as Euler diagrams can improve human reasoning performance.
By Risako Ando, Koji Mineshima
arXiv:2608. 12374v1 Announce Type: cross Abstract: Language models (LMs) struggle with logical tasks like reasoning on syllogisms.
By Hanna Abi Akl, Fabien Gandon, Catherine Faron, Pierre Monnin
arXiv:2606. 09157v1 Announce Type: cross Abstract: This paper revisits our pipeline called Syllogistic Evaluation Framework-Common Logic Grammar Construction (SEF-CLGC).
By Hanna Abi Akl, Fabien Gandon, Catherine Faron, Pierre Monnin
arXiv:2606. 03883v1 Announce Type: new Abstract: Large reasoning models (LRMs) are often evaluated using metrics such as final-answer accuracy or token count.
By Fr\'ed\'eric Berdoz, Luca A. Lanzend\"orfer, Fabian Farestam, Roger Wattenhofer
arXiv:2607. 23019v1 Announce Type: new Abstract: Chain-of-thought (CoT) prompting enables large language models (LLMs) to tackle multi-step reasoning tasks, yet the generated intermediate steps are not guaranteed to be logically sound.
By Zirong Chen, Meiyi Ma
arXiv:2606. 07515v1 Announce Type: cross Abstract: We investigate the probabilistic reasoning capabilities of large language models through a controlled benchmarking study on discrete probability problems.
By Luca Avena, Gianmarco Bet, Bernardo Busoni