Large Language Models (LLMs) have demonstrated exceptional capabilities across various natural language processing tasks. Yet, many of these advanced LLMs are tailored for broad, general-purpose applications. In this technical report, we introduce AcademicGPT, designed specifically to empower academic research. AcademicGPT is a continual training model derived from LLaMA2-70B. Our training corpus mainly consists of academic papers, thesis, content from some academic domain, high-quality Chinese data and others. While it may not be extensive in data scale, AcademicGPT marks our initial venture into a domain-specific GPT tailored for research area. We evaluate AcademicGPT on several established public benchmarks such as MMLU and CEval, as well as on some specialized academic benchmarks like PubMedQA, SCIEval, and our newly-created ComputerScienceQA, to demonstrate its ability from general knowledge ability, to Chinese ability, and to academic ability. Building upon AcademicGPT's foundation model, we also developed several applications catered to the academic area, including General Academic Question Answering, AI-assisted Paper Reading, Paper Review, and AI-assisted Title and Abstract Generation.

翻译：大型语言模型（LLMs）在多种自然语言处理任务中已展现出卓越能力。然而，这些先进的大语言模型大多面向通用的、泛化的应用场景。在本技术报告中，我们介绍AcademicGPT——一个专为赋能学术研究而设计的模型。AcademicGPT是基于LLaMA2-70B的持续训练模型，其训练语料主要包含学术论文、学位论文、部分学术领域内容、高质量中文数据及其他语料。尽管在数据规模上可能并不庞大，但AcademicGPT标志着我们首次尝试构建面向研究领域的专用GPT模型。我们分别在MMLU和CEval等多个权威公开基准，以及PubMedQA、SCIEval和自建数据集ComputerScienceQA等学术专用基准上对AcademicGPT进行评估，以验证其在通用知识能力、中文能力及学术能力方面的表现。基于AcademicGPT的基座模型，我们还开发了多项面向学术领域的应用功能，包括通用学术问答、AI辅助论文阅读、论文评审及AI辅助标题与摘要生成。