RRepoGEO

REPOGEO REPORT · LITE

Yaofang-Liu/Pusa-VidGen

Default branch main · commit 8a8c4f52 · scanned 6/1/2026, 4:42:01 AM

GitHub: 682 stars · 46 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 Yaofang-Liu/Pusa-VidGen, 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 the README's opening to clearly state the project's purpose and audience

    Why:

    CURRENT
    # Pusa: Thousands Timesteps Video Diffusion Model (ICLR 2026)
    COPY-PASTE FIX
    # Pusa: A Unified Video Diffusion Framework for Efficient, High-Quality Generation

Pusa introduces a groundbreaking paradigm leveraging vectorized timestep adaptation (VTA) to enable fine-grained temporal control within a unified video diffusion framework. Designed for AI researchers and practitioners, Pusa allows for efficient generation of high-quality, long-duration video content, building upon state-of-the-art models like Wan-T2V-14B.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://yaofang-liu.github.io/Pusa_Web/

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 Yaofang-Liu/Pusa-VidGen
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pika Labs
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pika Labs · recommended 2×
  2. RunwayML Gen-2 · recommended 2×
  3. Sora · recommended 1×
  4. stability-ai/SVD · recommended 1×
  5. Google Lumiere · recommended 1×
  • CATEGORY QUERY
    Need a cutting-edge video diffusion model for high-quality, long-duration content generation.
    you: not recommended
    AI recommended (in order):
    1. Sora
    2. Stable Video Diffusion (stability-ai/SVD)
    3. Pika Labs
    4. RunwayML Gen-2
    5. Google Lumiere
    6. Meta Make-A-Video

    AI recommended 6 alternatives but never named Yaofang-Liu/Pusa-VidGen. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I achieve lightning-fast video generation with diffusion models, even with complex architectures?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion
    2. SDXL Turbo
    3. LCM-LoRA
    4. diffusers
    5. FFmpeg
    6. AnimateDiff
    7. ModelScope Text-to-Video Diffusion Model
    8. Pika Labs
    9. RunwayML Gen-2
    10. DeepSpeed
    11. Accelerate
    12. TensorRT
    13. OpenVINO

    AI recommended 13 alternatives but never named Yaofang-Liu/Pusa-VidGen. 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 Yaofang-Liu/Pusa-VidGen?
    pass
    AI named Yaofang-Liu/Pusa-VidGen explicitly

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

  • If a team adopts Yaofang-Liu/Pusa-VidGen in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Yaofang-Liu/Pusa-VidGen 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 Yaofang-Liu/Pusa-VidGen solve, and who is the primary audience?
    pass
    AI did not name Yaofang-Liu/Pusa-VidGen — 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?

Embed your GEO score

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Yaofang-Liu/Pusa-VidGen — 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