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Large Language Models, Updates, and Evaluation of Automation Tools for Systematic Reviews: a Summary of Significant Discussions at the Eighth Meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR)

Systematic Reviews(2024)

Michigan State University | Bond University | EPPI Centre | Cochrane Netherlands | TU Wien | National Institute of Environmental Health Sciences

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Abstract
The eighth meeting of the International Collaboration for the Automation of Systematic Reviews (ICASR) was held on September 7 and 8, 2023, at the University College London, London, England. ICASR is an interdisciplinary group whose goal is to maximize the use of technology for conducting rapid, accurate, and efficient evidence synthesis, e.g., systematic reviews, evidence maps, and scoping reviews of scientific evidence. In 2023, the major themes discussed were understanding the benefits and harms of automation tools that have become available in recent years, the advantages and disadvantages of large language models in evidence synthesis, and approaches to ensuring the validity of tools for the proposed task.
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Key words
Automation tools,ChatGPT,Evidence synthesis,Large language models,Systematic reviews
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  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
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  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
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要点】:本文概述了2023年国际系统评价自动化合作组织(ICASR)第八次会议的重要讨论内容,主要涉及自动化工具的利弊、大型语言模型在证据合成中的应用及工具有效性的确保。

方法】:会议通过跨学科讨论的方式,评估和探讨了当前自动化工具和大型语言模型在系统评价中的实际应用和潜在影响。

实验】:文中未提供具体实验细节,但提到了会议讨论的内容和结果,未提及使用的数据集名称。