111:2

Trovato and Tobin, et al.

future challenges that lie ahead in LLMs evaluation. Our aim is to offer invaluable insights to researchers
in the realm of LLMs evaluation, thereby aiding the development of more proficient LLMs. Our key point
is that evaluation should be treated as an essential discipline to better assist the development of LLMs. We
consistently maintain the related open-source materials at: https://github.com/MLGroupJLU/LLM-eval-survey.
CCS Concepts: • General and reference → Surveys and overviews.
Additional Key Words and Phrases: large language models, evaluation, model assessment, benchmark
ACM Reference Format:
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang
Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, and Xing Xie. 2018. A Survey
on Evaluation of Large Language Models . J. ACM 37, 4, Article 111 (August 2018), 42 pages. https://doi.org/
XXXXXXX.XXXXXXX
ASurveyonEvaluationofLargeLanguageModels