Update README.md

README.md

@@ -1,3 +1,79 @@
----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+task_categories:
+- text-generation
+language:
+- zh
+size_categories:
+- n<1K
+tags:
+  - chinese
+  - math-word-problems
+  - true-false
+  - mathematical-reasoning
+modalities:
+  - text
+libraries: 
+  - Datasets
+---
+
+## Introduction
+MathToF is a Chinese mathematical reasoning dataset introduced in the paper **Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models.** 
+
+It contains **1,000 Chinese true-or-false math problems**, each annotated with a **binary label (True/False)** and a **detailed rationale**.
+
+## Dataset Structure
+
+### Data Fields
+- `qtype`: question type. In MathToF, this is typically `"JUDGE"`.
+- `quest_stem`: the main question content.
+  - `quest_stem.text`: the problem statement in Chinese.
+- `quest_ref`: reference answers and explanations.
+  - `quest_ref.texts`: the ground-truth label(s), typically `"True"` or `"False"`.
+  - `quest_ref.analyses`: the explanation(s), stored as a list.
+
+### Example
+
+```json
+{
+    "qtype": "JUDGE",
+    "quest_stem": {
+        "text": "三位数减三位数差一定是三位数。"
+    },
+    "quest_ref": {
+        "texts": [
+            "False"
+        ],
+        "analyses": [
+            "如两个三位数分别为:150，100。则150-100=50，其差50是两位数，故题干描述错误。"
+        ]
+    }
+}
+```
+
+### Dataset Statistics
+
+According to the paper, the question-type distribution of MathToF is:
+
+- Arithmetic: 675
+- Algebra: 61
+- Geometry: 197
+- Statistics: 37
+- Reasoning: 13
+- Others: 17
+
+Total: 1,000 questions.
+
+## Citation
+
+If you use this dataset, please cite the following paper:
+```
+@inproceedings{tan-etal-2025-teaching,
+  title = {Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models},
+  author = {Tan, Wenting and Chen, Dongxiao and Xue, Jieting and Wang, Zihao and Chen, Taijie},
+  booktitle = {Proceedings of the 31st International Conference on Computational Linguistics: Industry Track},
+  pages = {827--839},
+  year = {2025},
+  publisher = {Association for Computational Linguistics}
+}
+```