RRepoGEO

REPOGEO REPORT · LITE

thu-ml/unidiffuser

Default branch main · commit 845e14f7 · scanned 5/10/2026, 2:33:20 PM

GitHub: 1,481 stars · 91 forks

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 thu-ml/unidiffuser, 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
  • highreadme#1
    Reposition README opening to highlight "unified framework" differentiator

    Why:

    CURRENT
    ## UniDiffuser

Code and models for the paper "One Transformer Fits All Distributions in Multi-Modal Diffusion"
    COPY-PASTE FIX
    ## UniDiffuser: A Unified Diffusion Framework for All Multi-Modal Distributions

UniDiffuser is a novel unified diffusion framework designed to fit all distributions relevant to multi-modal data within a single model. This repository provides the code and models for our paper "One Transformer Fits All Distributions in Multi-Modal Diffusion," demonstrating how one transformer can handle image, text, text-to-image, image-to-text, and image-text pair generation.
  • mediumhomepage#2
    Add a homepage link to the project's Hugging Face Space

    Why:

    COPY-PASTE FIX
    https://huggingface.co/spaces/thu-ml/unidiffuser

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 thu-ml/unidiffuser
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Flamingo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Flamingo · recommended 1×
  2. DALL-E 3 · recommended 1×
  3. Stability-AI/stablediffusion · recommended 1×
  4. lllyasviel/ControlNet · recommended 1×
  5. picsart-ai-research/Text2Video-Zero · recommended 1×
  • CATEGORY QUERY
    How can I generate content across multiple modalities using a single diffusion model?
    you: not recommended
    AI recommended (in order):
    1. Flamingo
    2. DALL-E 3
    3. Stable Diffusion (Stability-AI/stablediffusion)
    4. ControlNet (lllyasviel/ControlNet)
    5. Text2Video-Zero (picsart-ai-research/Text2Video-Zero)
    6. Imagen
    7. AudioGen (facebookresearch/audiogen)
    8. Phenaki (google-research/phenaki)

    AI recommended 8 alternatives but never named thu-ml/unidiffuser. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best transformer-based diffusion models for multi-modal data synthesis?
    you: not recommended
    AI recommended (in order):
    1. NÜWA
    2. Make-A-Video
    3. Phenaki
    4. Imagen Video
    5. VQ-Diffusion
    6. Parti
    7. DALLE-3

    AI recommended 7 alternatives but never named thu-ml/unidiffuser. 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 thu-ml/unidiffuser?
    pass
    AI did not name thu-ml/unidiffuser — 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 thu-ml/unidiffuser in production, what risks or prerequisites should they evaluate first?
    pass
    AI named thu-ml/unidiffuser 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 thu-ml/unidiffuser solve, and who is the primary audience?
    pass
    AI named thu-ml/unidiffuser explicitly

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

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thu-ml/unidiffuser — 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