用智能助手+人工校验，加速文献综述流程
ProfOlaf: Semi-Automated Tool for Systematic Literature Reviews
- 结合大模型与人工筛选，自动收集和提炼论文关键信息
- 支持迭代式文献搜集，提升综述效率与可复现性
- 适合科研人员快速完成高质量文献综述
系统性综述和映射研究对整合现有成果、发现研究空白至关重要，但通常耗时耗力。现有工具仅支持部分环节，整体仍依赖人工且易出错。我们提出 ProfOlaf，一个半自动化工具，用于简化系统性综述流程并保持方法严谨性。ProfOlaf 支持人机协同的迭代雪球法文献收集，利用大语言模型辅助筛选文献、提取关键主题及回答内容相关问题。通过自动化与受控人工干预相结合，显著提升综述的效率、质量和可复现性。该工具可作为命令行工具或网页应用使用。演示视频见：https://youtu.be/R-gY4dJlN3s
原文摘要 · Abstract (English)
Systematic reviews and mapping studies are critical to synthesize research, identify gaps, and guide future work, but are often labor-intensive and time-consuming. Existing tools provide partial support for specific steps, leaving much of the process manual and error-prone. We present ProfOlaf, a semi-automated tool designed to streamline systematic reviews while maintaining methodological rigor. ProfOlaf supports iterative snowballing for article collection with human-in-the-loop filtering and uses large language models to help select articles, extract key topics, and answer queries about the content of articles. By combining automation with guided manual effort, ProfOlaf enhances the efficiency, quality, and reproducibility of systematic reviews across research fields. ProfOlaf can be used both as a CLI tool and in web application format. A video demonstrating ProfOlaf is available at: https://youtu.be/R-gY4dJlN3s
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