# ProgRAG

**Repository Path**: titanquestit/ProgRAG

## Basic Information

- **Project Name**: ProgRAG
- **Description**: No description available
- **Primary Language**: Java
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-11-18
- **Last Updated**: 2025-11-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# [AAAI 2026] ProgRAG: Hallucination-Resistant Progressive Retrieval and Reasoning over Knowledge Graphs
Codes for the paper titled ["ProgRAG: Hallucination-Resistant Progressive Retrieval and Reasoning over Knowledge Graphs"](https://arxiv.org/pdf/2511.10240), published in the 40th Annual AAAI Conference on Artificial Intelligence (AAAI'2026).

---

![model](source/model.png)

---
# How to run
## 1) Installation
```
# Create and activate a new environment
conda create -n ProgRAG python=3.8 -y
conda activate ProgRAG

# Install PyTorch with CUDA 11.8
conda install pytorch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1 pytorch-cuda=11.8 -c pytorch -c nvidia

# Install PyG (PyTorch Geometric)
conda install pyg -c pyg

# Install other dependencies
conda install ninja easydict pyyaml -c conda-forge
pip install transformers sentence-transformers
```

## 2) Download Datasets and Checkpoints
To run experiments, download the required Knowledge Graph datasets and checkpoints for:
- Relation Retriever
- Triple Retriever : GNN, MPNet
  
You can download all necessary files from the following Google Drive link:
https://drive.google.com/drive/folders/1BVvQRNTaLdONEeFauZfxPYQXQSpCVuNm?usp=drive_link

Alternatively, you can preprocess the datasets using the following commands:
```
python3 graph_preprocess.py
python3 GNN/get_emb.py
```
You can train the GNN and MPNet (Triple Retrievers) using the following commands:
```
python3 GNN/gnn_train.py
python3 MPNet/[dataset].sh 
```


## 3) Run
```
python main.py --dataset [DATASET_NAME]
```
Replace [DATASET_NAME] with the name of the dataset you want to use (e.g., webqsp, cwq, etc.).