  Existing studies explore the explainability of Grammatical Error Correction
(GEC) in a limited scenario, where they ignore the interaction between
corrections and explanations. To bridge the gap, this paper introduces the task
of EXplainable GEC (EXGEC), which focuses on the integral role of both
correction and explanation tasks. To facilitate the task, we propose EXCGEC, a
tailored benchmark for Chinese EXGEC consisting of 8,216 explanation-augmented
samples featuring the design of hybrid edit-wise explanations. We benchmark
several series of LLMs in multiple settings, covering post-explaining and
pre-explaining. To promote the development of the task, we introduce a
comprehensive suite of automatic metrics and conduct human evaluation
experiments to demonstrate the human consistency of the automatic metrics for
free-text explanations. All the codes and data will be released after the
review.
