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CORTEX framework structures web-scale corpora into knowledge graphs

Researchers have introduced CORTEX, a novel framework designed to organize web-scale corpora into structured knowledge graphs, moving beyond traditional flat document collections. This Ontological Corpus Graph (OCG) approach unifies a quality-refined content layer, an LLM-driven ontology layer, and a cross-domain alignment layer. The framework was used to create CortexBench, a benchmark that evaluated eight frontier LLMs, demonstrating the effectiveness of CORTEX in quality refinement, domain organization, and cross-domain data synthesis. AI

IMPACT This framework could enable more sophisticated and targeted training data for LLMs, potentially leading to improved model performance and specialized capabilities.

RANK_REASON The cluster describes a research paper detailing a new framework and benchmark for corpus organization.

Read on arXiv cs.CL →

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CORTEX framework structures web-scale corpora into knowledge graphs

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Chengtao Gan, Xiaoke Guo, Yushan Zhu, Zhaoyan Gong, Zhiqiang Liu, Songze Li, Huajun Chen, Wen Zhang ·

    CORTEX: High-Quality Cross-Domain Organization of Web-Scale Corpora through Ontological Corpus Graph

    arXiv:2606.30175v1 Announce Type: new Abstract: The continuous evolution of large language models drives escalating demands on data scale and quality, and as different training stages impose increasingly tailored data requirements, systematic organization of high-quality corpora …

  2. arXiv cs.CL TIER_1 English(EN) · Wen Zhang ·

    CORTEX: High-Quality Cross-Domain Organization of Web-Scale Corpora through Ontological Corpus Graph

    The continuous evolution of large language models drives escalating demands on data scale and quality, and as different training stages impose increasingly tailored data requirements, systematic organization of high-quality corpora becomes indispensable. Existing corpus construct…