信息通信技术与政策2026，Vol.52Issue(5)：2-9,8.DOI:10.12267/j.issn.2096-5931.2026.05.001
全生命周期需求视角的高质量数据集供给研究
Research on high-quality dataset supply from the perspective of full life cycle demand
樊威 1李荪 1闫树 1王甜甜 2曹峰1
作者信息
- 1. 中国信息通信研究院人工智能研究所,北京 100083
- 2. 中国信息通信研究院政策与经济研究所,北京 100083
- 折叠
摘要
Abstract
With the rapid iteration of artificial intelligence technology,model training has shifted from the stage of general-scale expansion to a new stage driven by industrial applications and supported by high-quality data.The type,quality and supply capacity of data directly determine the industry adaptability and practical effectiveness of models.Data demands vary across the full life cycle of large models,and there are still shortcomings in the supply of high-quality datasets for industrial scenarios.Based on this,the focus is placed on the full stages of large model pre-training,supervised fine-tuning,reinforcement alignment,and engineering application.This paper sorts out the data demands of each stage and the evolutionary trend from"scale-oriented"to"quality-oriented".The evolving trends of data needs at each stage are analyzed,the disparities in high-quality data supply between international and domestic standards are compared,and the shortcomings of China's utilization of public data,data openness,and annotation ecosystems are examined.Consequently,targeted measures are proposed to optimize data supply,aiming to break through the bottleneck of training data for large models and support the advancement of the artificial intelligence industry.关键词
高质量数据集建设/数据训练需求/训练数据瓶颈/供给差异Key words
construction of high-quality data sets/data training requirements/training data bottlenecks/supply differences分类
管理科学引用本文复制引用
樊威,李荪,闫树,王甜甜,曹峰..全生命周期需求视角的高质量数据集供给研究[J].信息通信技术与政策,2026,52(5):2-9,8.
