RRepoGEO

REPOGEO REPORT · LITE

microsoft/DialoGPT

Default branch master · commit 61194e44 · scanned 5/22/2026, 8:07:41 PM

GitHub: 2,422 stars · 352 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /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
2 / 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/DialoGPT, 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
  • highreadme#1
    Update README H1 to reflect current status and value

    Why:

    CURRENT
    # A State-of-the-Art Large-scale Pretrained Response Generation Model (DialoGPT)
    COPY-PASTE FIX
    # DialoGPT: A Historical Large-scale Pretrained Response Generation Model for Reproducibility and Research
  • highreadme#2
    Add a dedicated section on DialoGPT's current value proposition

    Why:

    COPY-PASTE FIX
    Add a new section (e.g., "Why Use DialoGPT Today?") immediately after the deprecation notice, explicitly stating its value for research reproducibility, historical comparisons, or specific niche applications where GODEL might not be suitable. Emphasize its role as a benchmark or for understanding earlier dialogue model architectures.
  • mediumhomepage#3
    Add project homepage URL to repository metadata

    Why:

    COPY-PASTE FIX
    https://www.microsoft.com/en-us/research/project/large-scale-pretraining-for-response-generation/

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/DialoGPT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
mistralai/mistral-src
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. mistralai/mistral-src · recommended 2×
  2. OpenAI GPT-4 / GPT-3.5 Turbo · recommended 1×
  3. Anthropic Claude · recommended 1×
  4. Google Gemini · recommended 1×
  5. Meta Llama 3 · recommended 1×
  • CATEGORY QUERY
    How can I build an AI model for realistic multi-turn dialogue generation?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5 Turbo
    2. Anthropic Claude
    3. Google Gemini
    4. Meta Llama 3
    5. Mistral AI
    6. Hugging Face Transformers (huggingface/transformers)
    7. Rasa (RasaHQ/rasa)

    AI recommended 7 alternatives but never named microsoft/DialoGPT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What pre-trained models are available for generating human-quality conversational text responses?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. GPT-3.5
    3. Claude 3
    4. Gemini
    5. Llama 2 (facebookresearch/llama)
    6. Mistral Large (mistralai/mistral-src)
    7. Mixtral 8x7B (mistralai/mistral-src)
    8. Cohere Command

    AI recommended 8 alternatives but never named microsoft/DialoGPT. 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/DialoGPT?
    pass
    AI did not name microsoft/DialoGPT — 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 microsoft/DialoGPT in production, what risks or prerequisites should they evaluate first?
    pass
    AI named microsoft/DialoGPT 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/DialoGPT solve, and who is the primary audience?
    pass
    AI named microsoft/DialoGPT 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 microsoft/DialoGPT. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
<a href="https://repogeo.com/en/r/microsoft/DialoGPT"><img src="https://repogeo.com/badge/microsoft/DialoGPT.svg" alt="RepoGEO" /></a>
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microsoft/DialoGPT — 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