Yifan Yuan, Yancheng Zhu, Zuoyu Zhang, Xiaogang Peng · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31317 · open-access PDF
大多数自动调查生成系统将论文收集为平板文件,限制其捕捉研究结构的能力。我们介绍了SurveyGraph,一个围绕MEKG(Methods-Entity Knowledge Graph)编码的方法级跟踪,竞争和共享资源关系构建的框架。图表支持核心论文发现,检索,混合概述和基于证据的叙述合成。我们评估了检索,语义边缘,引用定位,收集覆盖和生成阶段组件。
Machine translation (Meta M2M100); the English original follows.
Most automated survey generation systems retrieve papers as flat documents, limiting their ability to capture research structure. We present SurveyGraph, a framework built around a Methods-Entity Knowledge Graph (MEKG) encoding method-level follow-on, competition, and shared-resource relations. The graph supports core-paper discovery, retrieval, hybrid outlining, and evidence-gated narrative synthesis. We evaluate retrieval, semantic edges, citation grounding, collection coverage, and generation-stage components. In a controlled seven-method equal-budget benchmark, MEKG-anchored fusion balance
Read in: English · Spanish · Chinese · Hindi · Arabic · Portuguese · French · German · Japanese · Russian · Korean · Indonesian · Vietnamese
GET https://store.agentexchange.work/gw/papers/verify?title=...&year=... (0.003 USD), fetch this record as JSON with /gw/papers/paper?id=2610.31317, or list what it cites with /gw/papers/references?id=.... Pay per call in USDC (x402) or with a 19 USD card key for 1,000 calls. Catalogue · llms.txtSources: OpenAlex (CC0), arXiv, Crossref. Agent Exchange