Update README.md

README.md

@@ -49,26 +49,47 @@ A typical data instance has the following structure:
 ```
 
 ## Data Splits / Subsets
-
 There are 6 different subsets, 3 for CLEVR-Easy (CLEVR-Easy-K10, CLEVR-Easy-K30, CLEVR-Easy-K50) and 3 for CLEVR (CLEVR-4-K10, CLEVR-4-K30, CLEVR-4-K50). For CLEVR-Easy only color and shape are relevant for the digit mapping while for CLEVR also material and size relevant are. K indicates how many cells are empty in the sudoku, i.e. K10 means that there are 10 empty cells. Each subset contains 1,000 puzzles. Currently, there are no separate training/validation/test splits within each subset.
 
 # Dataset Creation
-
 ## Curation Rationale
 
 Goal: Combine the compositional “CLEVR”-style visual complexity with the logical constraints of Sudoku. This setup pushes models to perform both visual recognition (understanding shapes, colors, etc.) and abstract reasoning (solving Sudoku).
 
 ## Source Data
-
 Synthetic Generation: The images are created in a CLEVR-like manner, programmatically generated with variations in shape, color, position, etc.
 Sudoku Logic: Each puzzle is automatically generated and there exists exactly one solution to the puzzle.
 
 ## Annotations
-
 Automatic Generation: Since the dataset is synthetic, the puzzle solutions are known programmatically. No human annotation is required for the puzzle solutions.
 Attributes: Each digit (1–9) is associated with one or more visual properties (e.g., color = "red", shape = "cube"). These are also generated systematically.
 
 ## Personal and Sensitive Information
-
 None: The dataset is purely synthetic, containing no personal or demographic data.
 
+# Usage
+## Loading the Dataset
+
+Example usage:
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("AIML-TUDA/CLEVR-Sudoku", "CLEVR-Easy-K10")
+print(dataset[0])
+```
+
+The second argument ("CLEVR-Easy-K10", "CLEVR-Easy-K30", etc.) corresponds to the 6 different subsets.
+Each subset has 1,000 puzzles.
+
+# Citation
+
+If you use or reference this dataset in your work, please cite the following:
+```
+@article{stammer2024neural,
+  title={Neural Concept Binder},
+  author={Stammer, Wolfgang and W{\"u}st, Antonia and Steinmann, David and Kersting, Kristian},
+  journal={Advances in Neural Information Processing Systems},
+  year={2024}
+}
+```
+