Work

HANRAG

RAG
LangChain
LangGraph
Python

Implementation of the HANRAG framework (arXiv:2509.09713v1) for robust retrieval-augmented generation under noisy, multi-hop query conditions. Python, RAG, LangChain, LangGraph.

HANRAG - noise-resistant retrieval-augmented generation for multi-hop QA

HANRAG (Heuristic Accurate Noise-resistant Retrieval-Augmented Generation) is an open-source implementation of the framework from the paper arXiv:2509.09713v1. It tackles robust RAG when queries are noisy or require multi-hop reasoning.

Focus

  • Noise-resistant retrieval: Heuristics and filtering so retrieval stays useful under imperfect or ambiguous queries.
  • Multi-hop handling: Design that supports chaining retrieval and generation steps for complex questions.
  • LangChain / LangGraph: Built so it fits into existing RAG pipelines and can be extended with custom graphs.

The code is on GitHub and can be used as a reference implementation or integrated into production RAG stacks.