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📝 [docs] Update README with TexTeller 3.0 technical report and dataset release

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- Added technical report and dataset release announcements to changelog
- Updated both English and Chinese README files
- Reordered Docker badge in Chinese README for consistency

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
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OleehyO
2025-08-22 15:26:47 +08:00
parent 30f7e93c49
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2 changed files with 11 additions and 1 deletions
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README.md
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@@ -25,6 +25,8 @@ TexTeller was trained with **80M image-formula pairs** (previous dataset can be
>[!NOTE]
> If you would like to provide feedback or suggestions for this project, feel free to start a discussion in the [Discussions section](https://github.com/OleehyO/TexTeller/discussions).
---
<table>
@@ -59,6 +61,10 @@ TexTeller was trained with **80M image-formula pairs** (previous dataset can be
## 📮 Change Log
- [2025-08-15] We have published the [technical report](https://arxiv.org/abs/2508.09220) of TexTeller. The model evaluated on the Benchmark (which was trained from scratch and had its handwritten subset filtered based on the test set) is available at https://huggingface.co/OleehyO/TexTeller_en. **Please do not directly use the open-source version of TexTeller3.0 to reproduce the experimental results of handwritten formulas**, as this model includes the test sets of these benchmarks.
- [2025-08-15] We have open-sourced the [training dataset](https://huggingface.co/datasets/OleehyO/latex-formulas-80M) of TexTeller 3.0. Please note that the handwritten* subset of this dataset is collected from existing open-source handwritten datasets (including both training and test sets). If you need to use the handwritten* subset for your experimental ablation, please filter the test labels first.
- [2024-06-06] **TexTeller3.0 released!** The training data has been increased to **80M** (**10x more than** TexTeller2.0 and also improved in data diversity). TexTeller3.0's new features:
- Support scanned image, handwritten formulas, English(Chinese) mixed formulas.

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@@ -9,9 +9,9 @@
[![](https://img.shields.io/badge/API-文档-orange.svg?logo=read-the-docs)](https://oleehyo.github.io/TexTeller/)
[![arXiv](https://img.shields.io/badge/arXiv-2508.09200-b31b1b.svg?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2508.09220)
[![](https://img.shields.io/badge/docker-镜像-green.svg?logo=docker)](https://hub.docker.com/r/oleehyo/texteller)
[![](https://img.shields.io/badge/数据-TexTeller3.0-brightgreen.svg?logo=huggingface)](https://huggingface.co/datasets/OleehyO/latex-formulas-80M)
[![](https://img.shields.io/badge/权重-TexTeller3.0-yellow.svg?logo=huggingface)](https://huggingface.co/OleehyO/TexTeller)
[![](https://img.shields.io/badge/docker-镜像-green.svg?logo=docker)](https://hub.docker.com/r/oleehyo/texteller)
[![](https://img.shields.io/badge/协议-Apache_2.0-blue.svg?logo=github)](https://opensource.org/licenses/Apache-2.0)
</div>
@@ -59,6 +59,10 @@ TexTeller 使用 **8千万图像-公式对** 进行训练（前代数据集可
## 📮 更新日志
- [2025-08-15] 我们发布了 TexTeller 的[技术报告](https://arxiv.org/abs/2508.09220)。在基准集上评测的模型（从零训练，且对手写子集按测试集进行了过滤）可在 https://huggingface.co/OleehyO/TexTeller_en 获取。**请不要直接使用开源的 TexTeller3.0 版本来复现实验中的手写公式结果**，因为该模型的训练包含了这些基准的测试集。
- [2025-08-15] 我们开源了 TexTeller 3.0 的[训练数据集](https://huggingface.co/datasets/OleehyO/latex-formulas-80M)。其中handwritten* 子集来自现有的开源手写数据集（**包含训练集和测试集**），请不要将该子集用于实验消融。
- [2024-06-06] **TexTeller3.0 发布！** 训练数据增至 **8千万**（是 TexTeller2.0 的 **10倍** 并提升了数据多样性）。TexTeller3.0 新特性：
- 支持扫描件、手写公式、中英文混合公式识别