Update README.md

# GeoGen

Dataset of GeoExpand and GeoSynth for paper: [Enhancing the Geometric Problem-Solving Ability of Multimodal LLMsvia Symbolic-Neural Integration](https://arxiv.org/abs/2504.12773)
GitHub: [GeoGen](https://github.com/ycpNotFound/GeoGen)

## Features

- Build high-quality training data for internal MLLM to solve the problem of the lack of natural language CoT (Chain-of-Thought) explanation of existing data.
- GeoExpand focuses on expanding two classic geometry datasets: Geometry3K and PGPS9K.
- GeoSynth contains Q&A pairs and geometry diagrams that synthetized from scratch by random sampling predicates (e.g. geometric entity, `Triangle` or `Square`, and geometric relationship, `IsMidpointOfLine`).

## Statistics

From 4849 images in Geometry3K and PGPS9K, we generate 45,526 QA pairs, forming the GeoExpand dataset.

Using the Plotter module in GeoGen, we synthesize new geometric diagrams and generate CoT data in the same manner to construct GeoSynth:
- Sampled from 3,159 unique combinations of geometric predicates;
- Generated 129,230 diagrams;
After filtering and deduplication, retained 62,868 samples.

README.md

@@ -1,3 +1,10 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+- visual-question-answering
+language:
+- en
+pretty_name: GeoExpand & GeiSynth
+size_categories:
+- 10K<n<100K
+---