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 inter-event 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 EV2 for EValuation of EVent reasoning. EV2 consists of two levels of
evaluation of schema and instance and is comprehensive in relations and
reasoning paradigms. We conduct extensive experiments on EV2. 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
introduce two methods to guide the LLMs to utilize the event schema knowledge.
Both methods achieve improvements.

对 LLMs 的事件推理能力进行了综合评估，发现 LLMs 在事件推理方面的表现仍然不尽如人意。通过发现 LLMs 对事件推理能力存在的不平衡，提出了两种方法来指导 LLMs 利用事件模式知识，并获得了改进。