开放研究者：释放人工智能加速科学研究

OpenResearcher: Unleashing AI for Accelerated Scientific Research

August 13, 2024

作者: Yuxiang Zheng, Shichao Sun, Lin Qiu, Dongyu Ru, Cheng Jiayang, Xuefeng Li, Jifan Lin, Binjie Wang, Yun Luo, Renjie Pan, Yang Xu, Qingkai Min, Zizhao Zhang, Yiwen Wang, Wenjie Li, Pengfei Liu

cs.AI

摘要

科学文献的快速增长给研究人员带来了重大挑战，使他们难以跟上各领域最新进展并深入探索新领域。我们推出了OpenResearcher，这是一个创新平台，利用人工智能（AI）技术加速研究过程，回答研究人员提出的各种问题。OpenResearcher基于检索增强生成（RAG）构建，将大型语言模型（LLMs）与最新的领域特定知识整合在一起。此外，我们为OpenResearcher开发了各种工具，用于理解研究人员的查询，从科学文献中搜索，过滤检索到的信息，提供准确全面的答案，并自我完善这些答案。OpenResearcher可以灵活使用这些工具来平衡效率和有效性。因此，OpenResearcher使研究人员节省时间，增加发现新见解并推动科学突破的潜力。演示、视频和代码可在以下网址找到：https://github.com/GAIR-NLP/OpenResearcher。

English

The rapid growth of scientific literature imposes significant challenges for researchers endeavoring to stay updated with the latest advancements in their fields and delve into new areas. We introduce OpenResearcher, an innovative platform that leverages Artificial Intelligence (AI) techniques to accelerate the research process by answering diverse questions from researchers. OpenResearcher is built based on Retrieval-Augmented Generation (RAG) to integrate Large Language Models (LLMs) with up-to-date, domain-specific knowledge. Moreover, we develop various tools for OpenResearcher to understand researchers' queries, search from the scientific literature, filter retrieved information, provide accurate and comprehensive answers, and self-refine these answers. OpenResearcher can flexibly use these tools to balance efficiency and effectiveness. As a result, OpenResearcher enables researchers to save time and increase their potential to discover new insights and drive scientific breakthroughs. Demo, video, and code are available at: https://github.com/GAIR-NLP/OpenResearcher.