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SurveyAgent: A Conversational System for Personalized and Efficient Research Survey
April 10, 2024, 4:47 a.m. | Xintao Wang, Jiangjie Chen, Nianqi Li, Lida Chen, Xinfeng Yuan, Wei Shi, Xuyang Ge, Rui Xu, Yanghua Xiao
cs.CL updates on arXiv.org arxiv.org
Abstract: In the rapidly advancing research fields such as AI, managing and staying abreast of the latest scientific literature has become a significant challenge for researchers. Although previous efforts have leveraged AI to assist with literature searches, paper recommendations, and question-answering, a comprehensive support system that addresses the holistic needs of researchers has been lacking. This paper introduces SurveyAgent, a novel conversational system designed to provide personalized and efficient research survey assistance to researchers. SurveyAgent integrates …
abstract arxiv become challenge conversational cs.cl fields literature paper personalized question recommendations research researchers scientific support survey type
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