| license: cc-by-4.0 | |
| task_categories: | |
| - text-retrieval | |
| language: | |
| - en | |
| # 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}, | |
| } | |
| ``` |