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WisPaper: Your AI Scholar Search Engine
arXiv – CS AI|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||4 views
🤖AI Summary
WisPaper is a new AI-powered academic search system that combines semantic search capabilities with automated paper validation and organization tools. The system achieved 22.26% recall on TaxoBench and 93.70% validation accuracy, addressing key limitations in current academic search engines by integrating discovery, organization, and monitoring workflows.
Key Takeaways
- →WisPaper introduces an end-to-end AI agent system for academic literature discovery and organization.
- →The system combines rapid keyword search with deep semantic validation through the WisModel AI component.
- →WisPaper achieved 22.26% recall on TaxoBench, outperforming the O3 baseline of 20.92%.
- →The validation model attained 93.70% accuracy in verifying paper relevance to research queries.
- →The platform integrates three modules: Scholar Search, Library organization, and AI Feeds for continuous monitoring.
#ai-search#academic-research#semantic-search#ai-agent#research-tools#arxiv#machine-learning#validation-accuracy#scholarly-literature
Read Original →via arXiv – CS AI
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