Add paper link and task category

Hi! This PR improves the dataset card for CADBench by:
- Adding the relevant task category (`image-to-text`).
- Linking it to the associated paper: [CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation](https://huggingface.co/papers/2605.10873).
- Providing a summary of the dataset content, modalities, and metrics based on the paper abstract.

README.md

@@ -1,4 +1,6 @@
 ---
+task_categories:
+- image-to-text
 dataset_info:
   features:
   - name: file_id
@@ -58,3 +60,20 @@ configs:
   - split: bench0F
     path: data/bench0F-*
 ---
+
+# CADBench
+
+CADBench is a unified multimodal benchmark for AI-assisted CAD program generation, introduced in the paper [CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation](https://huggingface.co/papers/2605.10873).
+
+The benchmark contains 18,000 evaluation samples spanning six benchmark families derived from DeepCAD, Fusion 360, ABC, MCB, and Objaverse. It is designed to measure progress in editable 3D reconstruction and multimodal CAD understanding.
+
+### Dataset Summary
+
+CADBench supports evaluation across five input modalities:
+- **Clean meshes**
+- **Noisy meshes**
+- **Single-view renders**
+- **Photorealistic renders (PBR)**
+- **Multi-view renders**
+
+The benchmark evaluates models across six metrics covering geometric fidelity, executability, and program compactness. STEP-based families are stratified by B-rep face count to support controlled analysis across complexity and object variation.