Automated Literature Review Generator

This n8n workflow streamlines the process of conducting a literature review by automatically searching academic papers related to a specified topic within a given date range, sorting them by citation count, parsing their PDFs, summarizing key insights, and generating a comprehensive review document. Starting with user-defined parameters such as topic, year range, and maximum number of papers, the workflow searches across multiple scholarly databases like PubMed, Semantic Scholar, arXiv, and Google Scholar. It then sorts the papers by the number of citations, selects the top N papers, and parses their PDF content for further analysis. Using GPT-4, the workflow synthesizes summaries, methodologies, and main findings from each paper, combining these sections into a cohesive literature review. Finally, it exports the review as a Markdown file. This automation significantly accelerates academic research, helping researchers efficiently compile comprehensive literature reviews on complex topics.