[2512.06879] WisPaper: Your AI Scholar Search Engine
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Abstract page for arXiv paper 2512.06879: WisPaper: Your AI Scholar Search Engine
Computer Science > Information Retrieval arXiv:2512.06879 (cs) [Submitted on 7 Dec 2025 (v1), last revised 27 Feb 2026 (this version, v2)] Title:WisPaper: Your AI Scholar Search Engine Authors:Li Ju, Jun Zhao, Mingxu Chai, Ziyu Shen, Xiangyang Wang, Yage Geng, Chunchun Ma, Hao Peng, Guangbin Li, Tao Li, Chengyong Liao, Fu Wang, Xiaolong Wang, Junshen Chen, Rui Gong, Shijia Liang, Feiyan Li, Ming Zhang, Kexin Tan, Junjie Ye, Zhiheng Xi, Shihan Dou, Tao Gui, Yuankai Ying, Yang Shi, Yue Zhang, Qi Zhang View a PDF of the paper titled WisPaper: Your AI Scholar Search Engine, by Li Ju and 26 other authors View PDF Abstract:We present \textsc{WisPaper}, an end-to-end agent system that transforms how researchers discover, organize, and track academic literature. The system addresses two fundamental challenges. (1)~\textit{Semantic search limitations}: existing academic search engines match keywords but cannot verify whether papers truly address complex research questions; and (2)~\textit{Workflow fragmentation}: researchers must manually stitch together separate tools for discovery, organization, and monitoring. \textsc{WisPaper} tackles these through three integrated modules. \textbf{Scholar Search} combines rapid keyword retrieval with \textit{Deep Search}, in which an agentic model, \textsc{WisModel}, validates candidate papers against user queries through structured reasoning. Discovered papers flow seamlessly into \textbf{Library} with one click, where systematic organization...