Update README.md

README.md

@@ -1,15 +1,58 @@
-
 ---
-license: mit
+license: apache-2.0
+pretty_name: CountHalluSet — SimObject
+task_categories:
+  - image-generation
+  - counting-hallucinations
+size_categories:
+  - 10K<n<100K
 tags:
-- image-classification
+  - diffusion
+  - counting
+  - hallucination
+  - rendered
 ---
 
-# ToyShape Dataset
+# CountHalluSet — SimObject
+
+Rendered dataset from **[Counting Hallucinations in Diffusion Models](https://arxiv.org/abs/2510.13080)**
+(arXiv:2510.13080). Part of **CountHalluSet**, a suite with well-defined counting
+criteria used to measure *counting hallucination* — a diffusion model generating
+the wrong number of instances, even for patterns absent from its training data.
+
+## What's inside
+
+256×256 RGB **rendered images of everyday objects**, each labelled with the
+per-class instance count over three object classes. As with ToyShape, a correct
+sample contains at most one instance per class; extra or missing instances are
+counting hallucinations.
+
+```
+SimObject/
+├── images/       # 00000.png, 00001.png, ...
+└── labels.csv    # filename, <class_1>, <class_2>, <class_3>
+```
+
+<!-- TODO: fill in the three object class names (the labels.csv column headers)
+     and one line on how the images were rendered (renderer / asset source). -->
+
+## Usage
+
+```bash
+huggingface-cli download ShyFoo/CountHallu-dataset-SimObject \
+    --repo-type dataset --local-dir $DATASET_ROOT/SimObject
+```
 
-This is a toy dataset containing images of shapes.
+Load with the reference code (`counthallu.datasets.SimObject`). See the
+[CountHallu repository](<GITHUB_URL>) for training and the full evaluation protocol.
 
-## Dataset Structure
+## Citation
 
-- `image`: The image of the shape.
-- `label`: A multi-label list corresponding to the classes: mug, apple, clock.
+```bibtex
+@article{fu2025counting,
+  title={Counting Hallucinations in Diffusion Models},
+  author={Fu, Shuai and Zhou, Jian and Chen, Qi and Jing, Huang and Nguyen, Huy Anh and Liu, Xiaohan and Zeng, Zhixiong and Ma, Lin and Zhang, Quanshi and Wu, Qi},
+  journal={arXiv preprint arXiv:2510.13080},
+  year={2025}
+}
+```