Create README.md

README.md

@@ -0,0 +1,93 @@
+---
+task_categories:
+- multiple-choice
+- question-answering
+- visual-question-answering
+language:
+- en
+size_categories:
+- 1K<n<10K
+---
+# Dataset Card for MathVerse
+
+- [Dataset Description](https://huggingface.co/datasets/AI4Math/MathVerse/blob/main/README.md#dataset-description)
+- [Paper Information](https://huggingface.co/datasets/AI4Math/MathVerse/blob/main/README.md#paper-information)
+- [Dataset Examples](https://huggingface.co/datasets/AI4Math/MathVerse/blob/main/README.md#dataset-examples)
+- [Leaderboard](https://huggingface.co/datasets/AI4Math/MathVerse/blob/main/README.md#leaderboard)
+- [Citation](https://huggingface.co/datasets/AI4Math/MathVerse/blob/main/README.md#citation)
+
+## Dataset Description
+The capabilities of **Multi-modal Large Language Models (MLLMs)** in **visual math problem-solving** remain insufficiently evaluated and understood. We investigate current benchmarks to incorporate excessive visual content within textual questions, which potentially assist MLLMs in deducing answers without truly interpreting the input diagrams.
+
+<p align="center">
+    <img src="https://raw.githubusercontent.com/ZrrSkywalker/MathVerse/main/figs/fig1.png" width="90%"> <br>
+</p>
+
+To this end, we introduce **MathVerse**, an all-around visual math benchmark designed for an equitable and in-depth evaluation of MLLMs. We meticulously collect 2,612 high-quality, multi-subject math problems with diagrams from publicly available sources. Each problem is then transformed by human annotators into **six distinct versions**, each offering varying degrees of information content in multi-modality, contributing to **15K** test samples in total. This approach allows MathVerse to comprehensively assess ***whether and how much MLLMs can truly understand the visual diagrams for mathematical reasoning.*** 
+
+<p align="center">
+    <img src="https://raw.githubusercontent.com/ZrrSkywalker/MathVerse/main/figs/fig2.png" width="90%"> <br>
+    Six different versions of each problem in <b>MathVerse</b> transformed by expert annotators.
+</p>
+
+In addition, we propose a **Chain-of-Thought (CoT) Evaluation strategy** for a fine-grained assessment of the output answers. Rather than naively judging True or False, we employ GPT-4(V) to adaptively extract crucial reasoning steps, and then score each step with detailed error analysis, which can reveal the intermediate CoT reasoning quality by MLLMs.
+
+<p align="center">
+    <img src="https://raw.githubusercontent.com/ZrrSkywalker/MathVerse/main/figs/fig3.png" width="90%"> <br>
+    The two phases of the CoT evaluation strategy.
+</p>
+
+## Paper Information
+- Code: https://github.com/ZrrSkywalker/MathVerse
+- Project: https://mathverse-cuhk.github.io/
+- Visualization: https://mathverse-cuhk.github.io/#visualization
+- Leaderboard: https://mathverse-cuhk.github.io/#leaderboard
+
+## Dataset Examples
+🖱 Click to expand the examples for six problems versions within three subjects</summary>
+
+<details>
+<summary>🔍 Plane Geometry</summary>
+
+<p align="center">
+    <img src="https://raw.githubusercontent.com/ZrrSkywalker/MathVerse/main/figs/ver1.png" width="50%"> <br>
+</p>
+</details>
+
+<details>
+<summary>🔍 Solid Geometry</summary>
+
+<p align="center">
+    <img src="https://raw.githubusercontent.com/ZrrSkywalker/MathVerse/main/figs/ver2.png" width="50%"> <br>
+</p>
+</details>
+
+<details>
+<summary>🔍 Functions</summary>
+
+<p align="center">
+    <img src="https://raw.githubusercontent.com/ZrrSkywalker/MathVerse/main/figs/ver3.png" width="50%"> <br>
+</p>
+</details>
+
+## Leaderboard
+### Contributing to the Leaderboard
+
+🚨 The [Leaderboard](https://mathverse-cuhk.github.io/#leaderboard) is continuously being updated. 
+
+The evaluation instructions and tools will be released soon. For now, please send your results on the ***testmini*** set to this email: [email protected]. Please refer to the following template to prepare your result json file.
+
+- [output_testmini_template.json]()
+
+## Citation
+
+If you find **MathVerse** useful for your research and applications, please kindly cite using this BibTeX:
+
+```latex
+@inproceedings{zhang2024mathverse,
+  title={MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?},
+  author={Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Peng Gao, Hongsheng Li},
+  booktitle={arXiv},
+  year={2024}
+}
+```