摘要
由一名新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于人工智能的新报告。根据N ewsRx编辑在科罗拉多州奥罗拉的新闻报道，研究表明，"调查使用先进的自然语言处理模型，以简化耗时的学术手稿写作和审查过程"。这项研究的资金支持包括国家人类基因组研究所。新闻编辑们从科罗拉多大学医学院的研究中获得了一句话：“为此，我们将大型语言模型整合到Manubot出版生态系统中，为学术文本提出修订建议。我们基于人工智能的修订工作流程采用了一个即时生成器，将手稿元数据整合到模板中。”为语言年龄模型生成特定章节的说明。该模型随后生成每个段落的修订版供人类作者审阅。我们通过对现有手稿的5个案例研究来评估这一方法。我们的结果表明，这些模型尽管存在一定的局限性，但仍存在一定的局限性。可以掌握复杂的学术内容，提高文本质量。使用视觉控制系统跟踪手稿的所有变化，确保区分人工和机器生成的文本的透明度。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting out of Aurora, Colorado, by N ewsRx editors, research stated, “Investigate the use of advanced natural languag e processing models to streamline the time-consuming process of writing and revi sing scholarly manuscripts.” Financial supporters for this research include National Human Genome Research In stitute. The news editors obtained a quote from the research from University of Colorado School of Medicine: “For this purpose, we integrate large language models into t he Manubot publishing ecosystem to suggest revisions for scholarly texts. Our AI -based revision workflow employs a prompt generator that incorporates manuscript metadata into templates, generating section-specific instructions for the langu age model. The model then generates revised versions of each paragraph for human authors to review. We evaluated this methodology through 5 case studies of exis ting manuscripts, including the revision of this manuscript. Our results indicat e that these models, despite some limitations, can grasp complex academic concep ts and enhance text quality. All changes to the manuscript are tracked using a v ersion control system, ensuring transparency in distinguishing between human- an d machine-generated text.”
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