SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
Hengxing Cai, Xiaochen Cai, Junhan Chang, Sihang Li, Lin Yao, Wang Changxin, Zhifeng Gao, Hongshuai Wang
Abstract
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis. However, existing benchmarks fail to adequately evaluate the proficiency of LLMs in this domain, particularly in scenarios requiring higher-level abilities beyond mere memorization and the handling of multimodal data.In response to this gap, we introduce SciAssess, a benchmark specifically designed for the comprehensive evaluation of LLMs in scientific literature analysis. It aims to thoroughly assess the efficacy of LLMs by evaluating their capabilities in Memorization (L1), Comprehension (L2), and Analysis & Reasoning (L3). It encompasses a variety of tasks drawn from diverse scientific fields, including biology, chemistry, material, and medicine.To ensure the reliability of SciAssess, rigorous quality control measures have been implemented, ensuring accuracy, anonymization, and compliance with copyright standards. SciAssess evaluates 11 LLMs, highlighting their strengths and areas for improvement. We hope this evaluation supports the ongoing development of LLM applications in scientific literature analysis.SciAssess and its resources are available at https://github.com/sci-assess/SciAssess.
BibTeX
@inproceedings{cai-etal-2025-sciassess,
title = "{S}ci{A}ssess: Benchmarking {LLM} Proficiency in Scientific Literature Analysis",
author = "Cai, Hengxing and
Cai, Xiaochen and
Chang, Junhan and
Li, Sihang and
Yao, Lin and
Changxin, Wang and
Gao, Zhifeng and
Wang, Hongshuai and
Yongge, Li and
Lin, Mujie and
Yang, Shuwen and
Wang, Jiankun and
Xu, Mingjun and
Huang, Jin and
Fang, Xi and
Zhuang, Jiaxi and
Yin, Yuqi and
Li, Yaqi and
Chen, Changhong and
Cheng, Zheng and
Zhao, Zifeng and
Zhang, Linfeng and
Ke, Guolin",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-naacl.125/",
pages = "2335--2357",
ISBN = "979-8-89176-195-7"
}