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cs.AI2026
Are Large Reasoning Models Good Everyday Reasoners? A Comparison with Non-Reasoning Models on Logical Reasoning Tasks
Kentaro Ozeki, Risako Ando, Takanobu Morishita +3
Large reasoning models (LRMs) that leverage test-time computation achieve strong performance on mathematical and scientific benchmarks and are increasingly deployed in real-world a…
cs.CL2026
Abductive Reasoning with Syllogistic Forms in Large Language Models
Hirohiko Abe, Risako Ando, Takanobu Morishita Kentaro Ozeki +2
Research in AI using Large-Language Models (LLMs) is rapidly evolving, and the comparison of their performance with human reasoning has become a key concern. Prior studies have ind…
cs.CL2026
Evaluation of Deontic Conditional Reasoning in Large Language Models: The Case of Wason's Selection Task
Hirohiko Abe, Kentaro Ozeki, Risako Ando +3
As large language models (LLMs) advance in linguistic competence, their reasoning abilities are gaining increasing attention. In humans, reasoning often performs well in domain spe…