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README.md

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+---
+license: mit
+task_categories:
+- question-answering
+- text-generation
+language:
+- en
+tags:
+- math
+- reasoning
+- synthetic
+size_categories:
+- 1K<n<10K
+---
+
+# GSM-DC Test Dataset
+
+This dataset contains the test set for GSM-DC (Grade School Math with Distractor Chains), a synthetic math reasoning dataset with controlled complexity.
+
+## Dataset Details
+
+- **Total Problems**: 6300
+- **Operation Counts (OP)**: 16-22 (out-of-distribution test set)
+- **Problem Types**: Graph-based mathematical reasoning problems
+- **Noise Levels**: Light, Medium, Hard (distractor difficulty)
+
+## Dataset Structure
+
+Each problem in `all_problems.json` contains:
+- `problem_text`: The problem statement with all variables and relationships
+- `solution`: Step-by-step ground truth solution
+- `final_answer`: The numerical answer
+- `n_op`: Number of operations (16-22)
+- `noise_level`: Distractor difficulty (light/medium/hard)
+- `graph_structure`: Internal graph representation
+- `template_id`: Problem template identifier
+
+## Usage
+
+```python
+import json
+
+# Load the dataset
+with open('all_problems.json', 'r') as f:
+    problems = json.load(f)
+
+# Access a problem
+problem = problems[0]
+print(problem['problem_text'])
+print(problem['solution'])
+print(problem['final_answer'])
+```
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@inproceedings{gsm-dc-2025,
+    title={GSM-DC: Grade School Math with Distractor Chains},
+    author={[Your Name]},
+    booktitle={Proceedings of EMNLP 2025},
+    year={2025}
+}
+```
+
+## Paper
+
+Published at EMNLP 2025. [Paper Link]
+
+## License
+
+MIT License