RRepoGEO

REPOGEO REPORT · LITE

microsoft/ProphetNet

Default branch master · commit 5cf70eb4 · scanned 6/16/2026, 7:21:55 PM

GitHub: 748 stars · 117 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
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 microsoft/ProphetNet, 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 for better categorization

    Why:

    COPY-PASTE FIX
    natural-language-generation, nlg, transformer-models, diffusion-models, self-correcting-llms, research-project, deep-learning, pytorch
  • highreadme#2
    Reposition README H1 to clarify repo's focus on research implementations

    Why:

    CURRENT
    # A research project for natural language generation, containing the official implementations by MSRA NLC team.
    COPY-PASTE FIX
    # ProphetNet and Other Advanced Natural Language Generation Research Implementations by MSRA NLC Team
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    [Insert relevant project or team homepage URL here, e.g., a Microsoft Research page for NLC or ProphetNet]

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 microsoft/ProphetNet
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Llama 3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Llama 3 · recommended 1×
  2. Mixtral 8x7B Instruct · recommended 1×
  3. Gemma · recommended 1×
  4. Mistral 7B Instruct · recommended 1×
  5. Falcon 180B Instruct · recommended 1×
  • CATEGORY QUERY
    What are the best open-source models for advanced natural language generation tasks?
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mixtral 8x7B Instruct
    3. Gemma
    4. Mistral 7B Instruct
    5. Falcon 180B Instruct
    6. MPT-7B-Instruct / MPT-30B-Instruct

    AI recommended 6 alternatives but never named microsoft/ProphetNet. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I generate high-quality text using diffusion models or self-correcting LLMs?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Anthropic Claude
    3. Google Gemini
    4. Mistral AI
    5. Hugging Face Transformers Library
    6. Stable Diffusion

    AI recommended 6 alternatives but never named microsoft/ProphetNet. 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 microsoft/ProphetNet?
    pass
    AI named microsoft/ProphetNet explicitly

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

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

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

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microsoft/ProphetNet — 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