4 papers
Do Diagrams Help Large Language Models Reason? Evidence from Syllogistic Reasoning
Risako Ando, Koji Mineshima
Diagrams are widely used to support logical reasoning, and prior studies suggest that representations such as Euler diagrams can improve human reasoning performance. Recent work ha…
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…
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…
Normative Reasoning in Large Language Models: A Comparative Benchmark from Logical and Modal Perspectives
Kentaro Ozeki, Risako Ando, Takanobu Morishita +3
Normative reasoning is a type of reasoning that involves normative or deontic modality, such as obligation and permission. While large language models (LLMs) have demonstrated rema…