A Comprehensive Evaluation on Event Reasoning of Large Language Models

Event reasoning is a fundamental ability that underlies many applications. It requires event schema knowledge to perform global reasoning and needs to deal with the diversity of the interevent relations and the reasoning paradigms. How well LLMs accomplish event reasoning on various relations and reasoning paradigms remains unknown. To mitigate this disparity, we comprehensively evaluate the abilities of event reasoning of LLMs. We introduce a novel benchmark EV 2 for EValuation of EVent reasoning. EV 2 consists of two levels of evaluation of schema and instance and is comprehensive in relations and reasoning paradigms. We conduct extensive experiments on EV 2 . We find that LLMs have abilities to accomplish event reasoning but their performances are far from satisfactory. We also notice the imbalance of event reasoning abilities in LLMs. Besides, LLMs have event schema knowledge, however, they're not aligned with humans on how to utilize the knowledge. Based on these findings, we guide the LLMs in utilizing the event schema knowledge as memory leading to improvements on event reasoning. Code and Dataset are available on https://github.com/TZWwww/EV2 . Enjoy Life John decided to spend his Rebirth Day with his friends from various countries. Celebrate John invited guests to his home. His friends sang and danced together to their heart's content, telling stories under the string lights.