The exponential growth of scientific literature has resulted in information overload, challenging researchers to effectively synthesize relevant publications. This paper explores the integration of traditional reference management software with advanced computational techniques, including Large Language Models and Retrieval-Augmented Generation. We introduce PyZoBot, an AI-driven platform developed in Python, incorporating Zoteros reference management with OpenAIs sophisticated LLMs. PyZoBot streamlines knowledge extraction and synthesis from extensive human-curated scientific literature databases. It demonstrates proficiency in handling complex natural language queries, integrating data from multiple sources, and meticulously presenting references to uphold research integrity and facilitate further exploration. By leveraging LLMs, RAG, and human expertise through a curated library, PyZoBot offers an effective solution to manage information overload and keep pace with rapid scientific advancements. The development of such AI-enhanced tools promises significant improvements in research efficiency and effectiveness across various disciplines.

翻译：科学文献的指数级增长导致了信息过载，使研究人员难以有效综合相关出版物。本文探讨了传统参考文献管理软件与先进计算技术（包括大型语言模型和检索增强生成）的整合。我们介绍了PyZoBot，一个基于Python开发的AI驱动平台，该平台将Zotero的参考文献管理与OpenAI的先进LLMs相结合。PyZoBot简化了从大量人工策展的科学文献数据库中进行知识提取与综合的过程。它在处理复杂自然语言查询、整合多源数据以及精确呈现参考文献以维护研究诚信并促进进一步探索方面展现了卓越能力。通过利用LLMs、RAG及策展库所体现的人类专业知识，PyZoBot为管理信息过载、紧跟快速科学进展提供了有效解决方案。此类AI增强工具的开发有望显著提升各学科的研究效率与成效。