Add dataset card for GraphDancer

README.md

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+---
+license: cc-by-4.0
+task_categories:
+- text-generation
+language:
+- en
+tags:
+- graph-reasoning
+- llm-agent
+- curriculum-learning
+---
+
+# GraphDancer Dataset
+
+This repository contains the official training and evaluation data for **GraphDancer**, a framework for training Large Language Models (LLMs) to explore and reason over heterogeneous graphs via two-stage curriculum post-training.
+
+- **Paper:** [GraphDancer: Training LLMs to Explore and Reason over Graphs via Two-Stage Curriculum Post-Training](https://huggingface.co/papers/2602.02518)
+- **Project Page:** [https://yuyangbai.com/graphdancer/](https://yuyangbai.com/graphdancer/)
+- **Repository:** [https://github.com/leopoldwhite/GraphDancer](https://github.com/leopoldwhite/GraphDancer)
+
+## Dataset Summary
+
+The dataset provides multi-turn trajectories for graph-based reasoning tasks. It includes:
+- **Training Data:** Academic domain data used for both Curriculum-PPO and Curriculum-DPO stages.
+- **Test Data:** Evaluation sets across four domains from GRBench: Biomedical (Healthcare), Goodreads (Literature), Amazon (E-commerce), and Legal.
+
+## Sample Usage
+
+You can download the training and test data using the `huggingface_hub` library with the following script:
+
+```python
+from huggingface_hub import hf_hub_download
+import os, shutil
+
+repo_id = "yuyangbai/GraphDancer-data"
+
+os.makedirs("data/train", exist_ok=True)
+for domain in ["biomedical", "goodreads", "amazon", "legal"]:
+    os.makedirs(f"data/test/{domain}", exist_ok=True)
+
+# Download training data
+train_file = hf_hub_download(repo_id=repo_id, filename="train/train.parquet", repo_type="dataset")
+shutil.copy2(train_file, "data/train/train.parquet")
+
+# Download test data for each domain
+for domain in ["biomedical", "goodreads", "amazon", "legal"]:
+    test_file = hf_hub_download(repo_id=repo_id, filename=f"test/{domain}/test.parquet", repo_type="dataset")
+    shutil.copy2(test_file, f"data/test/{domain}/test.parquet")
+```
+
+## Structure
+
+The expected directory structure for the data is as follows:
+
+```text
+data/
+├── train/train.parquet          # Academic training set
+└── test/<domain>/test.parquet   # Per-domain test sets
+```
+
+## Citation
+
+```bibtex
+@misc{bai2026graphdancertrainingllmsexplore,
+      title={GraphDancer: Training LLMs to Explore and Reason over Graphs via Two-Stage Curriculum Post-Training},
+      author={Yuyang Bai and Zhuofeng Li and Ping Nie and Yu Wang and Jianwen Xie and Yu Zhang},
+      year={2026},
+      eprint={2602.02518},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG},
+      url={https://arxiv.org/abs/2602.02518},
+}
+```