REPOGEO REPORT · LITE
hhy-huang/HiRAG
Default branch main · commit 4d885ee1 · scanned 6/13/2026, 11:37:57 PM
GitHub: 547 stars · 82 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface hhy-huang/HiRAG, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition README opening to emphasize hierarchical RAG and dynamic refinement
Why:
CURRENTThis is the repo for the paper HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge. Accepted to EMNLP 2025 Findings!🎉Re-indexing the knowledge base is too costly🤯? Want to refine your knowledge base at test time? See our new work **DeepRefine**!
COPY-PASTE FIXHiRAG is a novel Retrieval-Augmented Generation (RAG) system designed to overcome the limitations of traditional flat RAG by leveraging **hierarchical knowledge structures** for superior generation quality. It uniquely addresses the high cost of re-indexing and enables **dynamic knowledge base refinement at test time**, offering a powerful solution for researchers and developers seeking advanced RAG capabilities. This is the official repository for our EMNLP 2025 Findings paper.
- mediumtopics#2Add more specific topics for hierarchical RAG and dynamic refinement
Why:
CURRENTclustering, graphrag, large-language-models, nlp, rag, retrieval-augmented-generation
COPY-PASTE FIXclustering, graphrag, large-language-models, nlp, rag, retrieval-augmented-generation, hierarchical-rag, dynamic-rag, knowledge-graph, knowledge-refinement
- lowhomepage#3Update homepage to arXiv abstract page
Why:
CURRENThttps://arxiv.org/pdf/2503.10150
COPY-PASTE FIXhttps://arxiv.org/abs/2503.10150
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- LlamaIndex · recommended 2×
- LangChain · recommended 2×
- Weaviate · recommended 2×
- Elasticsearch · recommended 2×
- Neo4j · recommended 1×
- CATEGORY QUERYLooking for a RAG system that leverages hierarchical knowledge for improved generation?you: not recommendedAI recommended (in order):
- LlamaIndex
- LangChain
- Neo4j
- Weaviate
- Elasticsearch
AI recommended 5 alternatives but never named hhy-huang/HiRAG. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat are efficient methods for updating or refining a RAG knowledge base dynamically?you: not recommendedAI recommended (in order):
- LlamaIndex
- LangChain
- Pinecone
- Weaviate
- Chroma
- Qdrant
- Elasticsearch
- Faiss
- Milvus
- Zilliz
AI recommended 10 alternatives but never named hhy-huang/HiRAG. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of hhy-huang/HiRAG?passAI named hhy-huang/HiRAG explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts hhy-huang/HiRAG in production, what risks or prerequisites should they evaluate first?passAI named hhy-huang/HiRAG explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo hhy-huang/HiRAG solve, and who is the primary audience?passAI named hhy-huang/HiRAG explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of hhy-huang/HiRAG. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
Live preview[](https://repogeo.com/en/r/hhy-huang/HiRAG)<a href="https://repogeo.com/en/r/hhy-huang/HiRAG"><img src="https://repogeo.com/badge/hhy-huang/HiRAG.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
hhy-huang/HiRAG — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite