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tags:
  - graph-rag
  - rag
  - large-language-models
  - knowledge-graph
  - prompt-engineering
license: mit
paperswithcode_id: propex-rag
arxiv: 2511.01802

PROPEX-RAG: Enhanced GraphRAG using Prompt Driven Prompt Execution

ProPEX-RAG is a prompt-driven, entity-guided RAG framework that emphasizes the role of prompt design in improving retrieval and reasoning across large knowledge graphs.

Our approach unifies symbolic graph construction with prompt-aware online retrieval, enabling precise entity extraction, fact filtering, and multi-hop passage re-ranking.

This design achieves high performance on complex QA tasks while maintaining scalability and efficiency, offering a practical and interpretable alternative to existing graph-based RAG systems.

Check out our papers to learn more:


Contact

Questions or issues? File an issue or contact Tejas Sarnaik

Citation

If you find this work useful, please consider citing our papers:

ProPEX-RAG

@article{sarnaik2025propex,
  title     = {PROPEX-RAG: Enhanced GraphRAG using Prompt-Driven Prompt Execution},
  author    = {Sarnaik, Tejas and Shah, Manan and Hegde, Ravi},
  journal   = {arXiv preprint arXiv:2511.01802},
  year      = {2025}