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New framework automates academic survey generation

Researchers have introduced DAS, a stateful agentic framework designed to automate the creation of academic surveys. This system separates paper analysis from manuscript construction, utilizing a dynamically updated metadata lake of approximately two million papers. DAS employs agents to manage literature, organization, writing, and finalization states, incorporating a semantic review process for efficient updates. A new benchmark, DAS-Bench, and evaluation metric, DAS-Eval, were also developed to assess the quality of generated surveys across various criteria. AI

IMPACT This framework could significantly streamline academic research by automating literature review and survey generation.

RANK_REASON Academic paper introducing a new framework and benchmark. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New framework automates academic survey generation

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Academic paper introducing a new framework and benchmark. [lever_c_demoted from research: ic=1 ai=1.0]
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46 days old
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Zhikai Xu, Zhucun Xue, Teng Hu, Yabiao Wang, Yong Liu, Jiangning Zhang ·

    Deep Academic Survey: Stateful Agentic Closed-Loop Paradigm for Academic Survey Automation

    arXiv:2608.18034v1 Announce Type: new Abstract: Academic surveys play a central role in organizing rapidly expanding scholarly literature, yet their construction requires extensive paper analysis, coherent knowledge organization, fine-grained citation support, and reliable manusc…