RRepoGEO

REPOGEO REPORT · LITE

danqi/acl2020-openqa-tutorial

Default branch master · commit 3c82cf3b · scanned 6/4/2026, 1:18:20 PM

GitHub: 835 stars · 88 forks

AI VISIBILITY SCORE
17 /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
1 / 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 danqi/acl2020-openqa-tutorial, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., LICENSE.md) in the repository root with the text of a suitable open-source license like MIT.
  • mediumhomepage#2
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    The URL for the tutorial video (e.g., from the ACL2020 proceedings or YouTube) or the official ACL2020 tutorial page.

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 danqi/acl2020-openqa-tutorial
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DPR
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. DPR · recommended 2×
  2. T5 · recommended 2×
  3. BART · recommended 2×
  4. RAG · recommended 1×
  5. REALM · recommended 1×
  • CATEGORY QUERY
    What are the cutting-edge models and techniques for open-domain question answering?
    you: not recommended
    AI recommended (in order):
    1. RAG
    2. REALM
    3. ATLAS
    4. Hugging Face Transformers RAG
    5. LangChain
    6. LlamaIndex
    7. Haystack
    8. GPT-4
    9. Claude 3
    10. Gemini
    11. DPR
    12. ColBERT
    13. ANCE
    14. T5
    15. BART
    16. Flan-T5
    17. DrQA
    18. ORQA

    AI recommended 18 alternatives but never named danqi/acl2020-openqa-tutorial. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Explain the different architectural approaches for building open-domain question answering systems.
    you: not recommended
    AI recommended (in order):
    1. Elasticsearch
    2. Hugging Face Transformers (huggingface/transformers)
    3. BERT
    4. RoBERTa
    5. T5
    6. LLaMA 2
    7. Mistral
    8. Pinecone
    9. OpenAI GPT-4
    10. Weaviate (weaviate/weaviate)
    11. Haystack (deepset-ai/haystack)
    12. Google Gemini
    13. Anthropic Claude 3
    14. DPR
    15. BART
    16. DBpedia
    17. SPARQL
    18. Wikidata
    19. Blazegraph (blazegraph/database)

    AI recommended 19 alternatives but never named danqi/acl2020-openqa-tutorial. 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 danqi/acl2020-openqa-tutorial?
    pass
    AI did not name danqi/acl2020-openqa-tutorial — likely talking about a different project

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

  • If a team adopts danqi/acl2020-openqa-tutorial in production, what risks or prerequisites should they evaluate first?
    pass
    AI named danqi/acl2020-openqa-tutorial 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 danqi/acl2020-openqa-tutorial solve, and who is the primary audience?
    pass
    AI did not name danqi/acl2020-openqa-tutorial — likely talking about a different project

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

Embed your GEO score

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danqi/acl2020-openqa-tutorial — 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