example

README.md

@@ -45,8 +45,6 @@ default_config_name: UltraData-Math-L3-Conversation-Synthetic
 
 ***UltraData-Math*** is a large-scale, high-quality mathematical pre-training dataset totaling **290B+ tokens** across three progressive tiers—**L1** (170.5B tokens web corpus), **L2** (33.7B tokens quality-selected), and **L3** (88B tokens multi-format refined)—designed to systematically enhance mathematical reasoning in LLMs. It has been applied to the mathematical pre-training of the [MiniCPM Series](https://huggingface.co/collections/openbmb/minicpm4) models.
 
-It was introduced in the paper [Data Science and Technology Towards AGI Part I: Tiered Data Management](https://huggingface.co/papers/2602.09003).
-
 ## 🆕 What's New
 
 - **[2026.02.09]**: **UltraData-Math**, a large-scale high-quality mathematical pre-training dataset with 290B+ tokens across three progressive tiers (L1/L2-preview/L3), is now available on Hugging Face. Released as part of the [UltraData](https://ultradata.openbmb.cn/) ecosystem. 🔥🔥🔥
@@ -208,7 +206,7 @@ If you find **UltraData-Math** useful in your research, please consider citing:
 ```bibtex
 @misc{ultradata-math,
   title={UltraData-Math},
-  author={Chuyue Zhou and Hongya Lyu and Xinle Lin and Yudong Wang and Jie Zhou and Hengyu Zhao and Junshao Guo and Xueren Zhang and Shuaikang Xue and Zhiyuan Liu},
+  author={UltraData Team},
   year={2026},
   url={https://huggingface.co/datasets/openbmb/UltraData-Math},
   publisher={Hugging Face}

README_ZH.md

@@ -166,7 +166,7 @@ ds = load_dataset("openbmb/UltraData-Math", "UltraData-Math-L3-Conversation-Synt
 ```bibtex
 @misc{ultradata-math,
   title={UltraData-Math},
-  author={Chuyue Zhou and Hongya Lyu and Xinle Lin and Yudong Wang and Jie Zhou and Hengyu Zhao and Junshao Guo and Xueren Zhang and Shuaikang Xue and Zhiyuan Liu},
+  author={UltraData Team},
   year={2026},
   url={https://huggingface.co/datasets/openbmb/UltraData-Math},
   publisher={Hugging Face}