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---
license: mit
task_categories:
- table-question-answering
language:
- en
tags:
- rag
- tables
- multi-table
- question-answering
- fact-checking
- llm
configs:
- config_name: table
data_files: tabfact_table.jsonl
- config_name: test_query
data_files: tabfact_query.jsonl
---
📄 [RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking](https://arxiv.org/abs/2504.01346) | 👨🏻💻 [Code](https://github.com/jiaruzouu/T-RAG) | 🤗 [MultiTableQA Hub Collection](https://huggingface.co/collections/jiaruz2/multitableqa-68dc8d850ea7e168f47cecd8)
This repository contains **MultiTableQA-TabFact**, one of the five datasets released as part of the comprehensive **MultiTableQA** benchmark. MultiTableQA-TabFact focuses on **table fact-checking** tasks. The overall MultiTableQA benchmark extends the traditional single-table QA setting into a multi-table retrieval and question answering benchmark, enabling more realistic and challenging evaluations.
Other datasets in the MultiTableQA benchmark include:
| Dataset | Link |
|-----------------------|------|
| MultiTableQA-TATQA | 🤗 [dataset link](https://huggingface.co/datasets/jiaruz2/MultiTableQA_TATQA) |
| MultiTableQA-TabFact | 🤗 [dataset link](https://huggingface.co/datasets/jiaruz2/MultiTableQA_TabFact) |
| MultiTableQA-SQA | 🤗 [dataset link](https://huggingface.co/datasets/jiaruz2/MultiTableQA_SQA) |
| MultiTableQA-WTQ | 🤗 [dataset link](https://huggingface.co/datasets/jiaruz2/MultiTableQA_WTQ) |
| MultiTableQA-HybridQA | 🤗 [dataset link](https://huggingface.co/datasets/jiaruz2/MultiTableQA_HybridQA)|
---
### Sample Usage
To download and preprocess the **MultiTableQA** benchmark, navigate to the `table2graph` directory in the code repository and run the `prepare_data.sh` script:
```bash
cd table2graph
bash scripts/prepare_data.sh
```
This script will automatically fetch the source tables, apply decomposition (row/column splitting), and generate the benchmark splits.
---
# Citation
If you find our work useful, please cite:
```bibtex
@misc{zou2025rag,
title={RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking},
author={Jiaru Zou and Dongqi Fu and Sirui Chen and Xinrui He and Zihao Li and Yada Zhu and Jiawei Han and Jingrui He},
year={2025},
eprint={2504.01346},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2504.01346},
}
``` |