1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CV2026★ 1 cited
MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale
Bin Wang, Tianyao He, Linke Ouyang +40
Current document parsing methods advance primarily through model architecture innovation, while systematic engineering of training data remains underexplored. Yet state-of-the-art…
cs.CV2025
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
Junbo Niu, Zheng Liu, Zhuangcheng Gu +58
We introduce MinerU2.5, a 1.2B-parameter document parsing vision-language model that achieves state-of-the-art recognition accuracy while maintaining exceptional computational effi…
cs.CL2025
WanJuanSiLu: A High-Quality Open-Source Webtext Dataset for Low-Resource Languages
Jia Yu, Fei Yuan, Rui Min +20
This paper introduces the open-source dataset WanJuanSiLu, designed to provide high-quality training corpora for low-resource languages, thereby advancing the research and developm…