RRepoGEO

REPOGEO REPORT · LITE

lupantech/ScienceQA

Default branch main · commit 2cbf8318 · scanned 6/4/2026, 5:57:12 AM

GitHub: 735 stars · 67 forks

AI VISIBILITY SCORE
68 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
Rule findings
1 pass · 1 warn · 0 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 lupantech/ScienceQA, 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 improve categorization for model training

    Why:

    COPY-PASTE FIX
    multimodal-ai, question-answering, scientific-reasoning, thought-chains, explanation-generation, large-language-models, vision-language-models, dataset, benchmark, neurips-2022
  • mediumhomepage#2
    Add the project homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://scienceqa.github.io
  • lowreadme#3
    Refine the README's opening sentence to emphasize model development

    Why:

    CURRENT
    Data and code for NeurIPS 2022 Paper "Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering".
    COPY-PASTE FIX
    This repository provides the data and code for "Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering" (NeurIPS 2022), designed to help researchers develop and train AI models for scientific reasoning.

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
1 / 2
50% of queries surface lupantech/ScienceQA
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
5%
Of all named tools, what % are you?
Top rival
VQA-E
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. VQA-E · recommended 1×
  2. A-OKVQA · recommended 1×
  3. GQA · recommended 1×
  4. OK-VQA · recommended 1×
  5. OpenAI GPT-4 · recommended 1×
  • CATEGORY QUERY
    Where can I find datasets and code for multimodal science question answering with explanations?
    you: #1
    AI recommended (in order):
    1. ScienceQA ← you
    2. VQA-E
    3. A-OKVQA
    4. GQA
    5. OK-VQA
    Show full AI answer
  • CATEGORY QUERY
    How to train AI models to generate step-by-step reasoning for complex scientific questions?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. GPT-3.5 Turbo
    3. Google PaLM 2
    4. Gemini
    5. Hugging Face Transformers Library
    6. Llama 2
    7. Falcon
    8. Mistral
    9. DeepMind AlphaCode
    10. AlphaGeometry
    11. SymPy
    12. Wolfram Alpha
    13. Z3
    14. Microsoft Guidance
    15. LangChain
    16. LlamaIndex

    AI recommended 16 alternatives but never named lupantech/ScienceQA. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 lupantech/ScienceQA?
    pass
    AI named lupantech/ScienceQA explicitly

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

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

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

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lupantech/ScienceQA — 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