RRepoGEO

REPOGEO REPORT · LITE

Alibaba-NLP/ViDoRAG

Default branch main · commit 2c1ec39c · scanned 5/31/2026, 9:37:48 AM

GitHub: 661 stars · 49 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

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 Alibaba-NLP/ViDoRAG, 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.

OVERALL DIRECTION
  • hightopics#1
    Add specific topics to the repository

    Why:

    COPY-PASTE FIX
    retrieval-augmented-generation, rag, multimodal-rag, visual-documents, document-ai, llm-framework, multi-agent-system, nlp, emnlp-2025
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0).
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    Add `https://arxiv.org/abs/2502.18017` as the homepage URL for the repository.

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.

Recall
0 / 2
0% of queries surface Alibaba-NLP/ViDoRAG
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-4o
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4o · recommended 1×
  2. GPT-4V · recommended 1×
  3. haotian-liu/LLaVA · recommended 1×
  4. adept/fuyu-8b · recommended 1×
  5. naver-ai/donut · recommended 1×
  • CATEGORY QUERY
    How to improve RAG performance on visually rich documents with iterative reasoning?
    you: not recommended
    AI recommended (in order):
    1. GPT-4o
    2. GPT-4V
    3. LLaVA (haotian-liu/LLaVA)
    4. Fuyu-8B (adept/fuyu-8b)
    5. Donut (naver-ai/donut)
    6. Nougat (facebookresearch/nougat)
    7. LayoutLMv3 (microsoft/unilm)
    8. Pix2Struct (google-research/pix2struct)

    AI recommended 8 alternatives but never named Alibaba-NLP/ViDoRAG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks integrate visual and textual retrieval for robust RAG in large document corpuses?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. Azure AI Search
    5. Google Cloud Vertex AI Search
    6. Weaviate
    7. Pinecone

    AI recommended 7 alternatives but never named Alibaba-NLP/ViDoRAG. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

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 Alibaba-NLP/ViDoRAG?
    pass
    AI named Alibaba-NLP/ViDoRAG explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Alibaba-NLP/ViDoRAG in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Alibaba-NLP/ViDoRAG 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 Alibaba-NLP/ViDoRAG solve, and who is the primary audience?
    pass
    AI named Alibaba-NLP/ViDoRAG explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Alibaba-NLP/ViDoRAG — 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