hhy-huang/HiRAG
[EMNLP'25 findings] This is the official repo for the paper, HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge.
This project helps you get more accurate and comprehensive answers from large language models (LLMs) when querying your specific documents or knowledge base. You provide your textual content, and it processes it to enable a system that understands the hierarchical relationships within your information. The result is a more insightful and detailed response to your questions. This is for data scientists, researchers, or anyone building advanced question-answering systems over their proprietary data.
522 stars.
Use this if you need to build a question-answering system over your domain-specific text data where the relationships and hierarchy of information are important for generating high-quality, detailed responses.
Not ideal if you are looking for a simple keyword search tool or if your data does not have inherent hierarchical structures that would benefit a more complex retrieval method.
Stars
522
Forks
83
Language
Python
License
MIT
Category
Last pushed
Nov 19, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/hhy-huang/HiRAG"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
NirDiamant/RAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG)...
VectorInstitute/fed-rag
A framework for fine-tuning retrieval-augmented generation (RAG) systems.
RUC-NLPIR/FlashRAG
⚡FlashRAG: A Python Toolkit for Efficient RAG Research (WWW2025 Resource)
ictnlp/FlexRAG
FlexRAG: A RAG Framework for Information Retrieval and Generation.
Andrew-Jang/RAGHub
A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and...