開放研究者：釋放人工智慧加速科學研究

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

科學文獻的快速增長給研究人員帶來了重大挑戰，他們需要不斷更新自己的領域中最新進展並深入探索新領域。我們介紹了一個創新平台OpenResearcher，該平台利用人工智慧（AI）技術來加速研究過程，回答研究人員提出的各種問題。OpenResearcher基於檢索增強生成（RAG）構建，將大型語言模型（LLMs）與最新的領域特定知識相結合。此外，我們為OpenResearcher開發了各種工具，用於理解研究人員的查詢、從科學文獻中搜索、過濾檢索到的信息、提供準確全面的答案並自我完善這些答案。OpenResearcher可以靈活使用這些工具來平衡效率和效果。因此，OpenResearcher使研究人員節省時間，增加發現新見解並推動科學突破的潛力。演示、視頻和代碼可在以下鏈接找到：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.