RRepoGEO

REPOGEO REPORT · LITE

kuleshov-group/mdlm

Default branch master · commit c112c526 · scanned 6/9/2026, 4:28:17 PM

GitHub: 696 stars · 98 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 kuleshov-group/mdlm, 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
  • highabout#1
    Clarify the project's domain in the 'About' description

    Why:

    CURRENT
    [NeurIPS 2024] Simple and Effective Masked Diffusion Language Model
    COPY-PASTE FIX
    [NeurIPS 2024] Simple and Effective Masked Diffusion Language Model for state-of-the-art text generation.
  • highreadme#2
    Move the core definition of MDLM to the very top of the README

    Why:

    COPY-PASTE FIX
    Move the paragraph starting with "We introduce *MDLM*, a **M**asked discrete **D**iffusion **L**anguage **M**odel..." to immediately follow the H1 and author list, before any links or update notices.
  • mediumtopics#3
    Add more specific topics to improve category visibility

    Why:

    CURRENT
    diffusion-language-models, diffusion-models, language-model, text
    COPY-PASTE FIX
    diffusion-language-models, diffusion-models, language-model, text, text-generation, masked-language-modeling, natural-language-generation, neurips-2024

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 kuleshov-group/mdlm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. diffusers · recommended 1×
  3. PyTorch · recommended 1×
  4. TensorFlow · recommended 1×
  5. Keras · recommended 1×
  • CATEGORY QUERY
    How can I build a language model using masked diffusion for text generation?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. diffusers
    3. PyTorch
    4. TensorFlow
    5. Keras
    6. JAX
    7. Flax
    8. OpenAI's Diffusion-LM

    AI recommended 8 alternatives but never named kuleshov-group/mdlm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best text generation models using diffusion for SOTA perplexity?
    you: not recommended
    AI recommended (in order):
    1. Diffusion-LM
    2. D3PM
    3. Diffusion-BERT
    4. Masked Diffusion Transformer
    5. Diffusion-GAN

    AI recommended 5 alternatives but never named kuleshov-group/mdlm. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 kuleshov-group/mdlm?
    pass
    AI did not name kuleshov-group/mdlm — 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 kuleshov-group/mdlm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kuleshov-group/mdlm 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 kuleshov-group/mdlm solve, and who is the primary audience?
    pass
    AI named kuleshov-group/mdlm explicitly

    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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MARKDOWN (README)
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HTML
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kuleshov-group/mdlm — 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