Update dataset card with metadata, links, and sample usage

README.md

@@ -1,5 +1,48 @@
 ---
 license: cc-by-4.0
+task_categories:
+- text-retrieval
+language:
+- en
 ---
 
-The dataset used in CiteGuard: Faithful Citation Attribution for LLMs via Retrieval-Augmented Validation https://www.arxiv.org/abs/2510.17853.
+# CiteGuard Dataset
+
+CiteGuard is a benchmark and framework used in the paper [CiteGuard: Faithful Citation Attribution for LLMs via Retrieval-Augmented Validation](https://huggingface.co/papers/2510.17853). It reframes citation evaluation as a problem of citation attribution alignment, assessing whether LLM-generated citations match those a human author would include for the same text.
+
+- **Project Page:** https://kathcym.github.io/CiteGuard_Page/
+- **GitHub Repository:** https://github.com/KathCYM/CiteGuard
+
+## Dataset Format
+
+The dataset follows a CSV format with the following columns:
+
+- `id`: Unique identifier for the excerpt.
+- `excerpt`: The text containing the citation to be validated (e.g., using a `[CITATION]` placeholder).
+- `year`: The year of the source paper.
+- `source_paper_title` (optional): The title of the paper containing the excerpt.
+- `target_paper_title` (optional): The gold standard title(s) for evaluation.
+
+## Sample Usage
+
+Using the [CiteGuard repository](https://github.com/KathCYM/CiteGuard), you can run the evaluation on a dataset file via the CLI:
+
+```bash
+python -m src.main --model_name gpt-4o --dataset DATASET.csv --result_path results/run.json
+```
+
+## Citation
+
+If you use this dataset or the CiteGuard framework, please cite the following:
+
+```bibtex
+@misc{choi2026citeguardfaithfulcitationattribution,
+      title={CiteGuard: Faithful Citation Attribution for LLMs via Retrieval-Augmented Validation}, 
+      author={Yee Man Choi and Xuehang Guo and Yi R. Fung and Qingyun Wang},
+      year={2026},
+      eprint={2510.17853},
+      archivePrefix={arXiv},
+      primaryClass={cs.DL},
+      url={https://arxiv.org/abs/2510.17853}, 
+}
+```