WoW：面向 LLM 全生命周期训练的大规模世界知识语料库

The WoW: A Large-Scale World Knowledge Corpus for Full-Lifecycle LLM Training

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WoW 是一个面向基础模型全周期训练的大规模中文教育数据集，以教育知识图谱为分类骨架，系统采集并补全各学段缺失的教育模块。相比此前版本，该版本系统性更强、质量更高、规模更大，并引入多模态信号，实验显示其在多项 benchmark 上显著提升模型表现。团队还提供基于图谱的数据选择与检索交互平台。

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Abstract:Existing Chinese educational corpora often suffer from fragmented coverage and a lack of systematic organization. In this paper, we propose WoW (\textbf{Wo}rld Kno\textbf{w}ledge), a large-scale dataset designed for the full-cycle training of foundation models. The construction of this dataset is driven by an Educational Knowledge Graph, which serves as a taxonomic backbone for the systematic collection and completion of missing educational modules across all levels. Compared to previous versions, this iteration provides enhanced systematicity, superior quality, and a larger scale, while incorporating multimodal signals and supporting every stage of model development. Experiments demonstrate that WoW significantly improves model performance across diverse benchmarks. To facilitate community research, we further provide an interactive platform for graph-based data selection and retrieval.

Subjects:	Artificial Intelligence (cs.AI)
Cite as:	arXiv:2611.13487 [cs.AI]
	(or arXiv:2611.13487v1 [cs.AI] for this version)
	https://doi.org/10.48550/arXiv.2611.13487 arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Tianze Sun [view email]
[v1] Tue, 10 Nov 2026 02:56:20 UTC (1,566 KB)

来源：arXiv cs.AI · arxiv.org