Update README.md

README.md

@@ -18,11 +18,13 @@ configs:
   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)
+📄 [Paper](https://arxiv.org/abs/2504.01346) | 👨🏻‍💻 [Code](https://github.com/jiaruzouu/T-RAG)
 
-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.
+## 🔍 Introduction
 
-Other datasets in the MultiTableQA benchmark include:
+Retrieval-Augmented Generation (RAG) has become a key paradigm to enhance Large Language Models (LLMs) with external knowledge. While most RAG systems focus on **text corpora**, real-world information is often stored in **tables** across web pages, Wikipedia, and relational databases. Existing methods struggle to retrieve and reason across **multiple heterogeneous tables**.
+
+For MultiTableQA, we release a comprehensive benchmark, including five different datasets covering table fact-checking, single-hop QA, and multi-hop QA: 
 | Dataset              | Link |
 |-----------------------|------|
 | MultiTableQA-TATQA    | 🤗 [dataset link](https://huggingface.co/datasets/jiaruz2/MultiTableQA_TATQA)   |
@@ -31,18 +33,8 @@ Other datasets in the MultiTableQA benchmark include:
 | 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.
+MultiTableQA extends the traditional single-table QA setting into a multi-table retrieval and question answering benchmark, enabling more realistic and challenging evaluations.
 
 ---
 # Citation