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 Hengyu Zhao and Junshao Guo and Xueren Zhang and Shuaikang Xue and Qiang Ma and Jie Zhou and Yudong Wang 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 Hengyu Zhao and Junshao Guo and Xueren Zhang and Shuaikang Xue and Qiang Ma and Jie Zhou and Yudong Wang and Zhiyuan Liu},
+  author={UltraData Team},
   year={2026},
   url={https://huggingface.co/datasets/openbmb/UltraData-Math},
   publisher={Hugging Face}