RRepoGEO

REPOGEO REPORT · LITE

lichao-sun/SoraReview

Default branch main · commit ae3f09fa · scanned 6/6/2026, 1:43:29 PM

GitHub: 504 stars · 20 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 lichao-sun/SoraReview, 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 to clarify the repo's nature as a review paper

    Why:

    COPY-PASTE FIX
    review-paper, survey-paper, sora, large-vision-models, generative-ai, video-generation, ai-research, openai
  • highlicense#2
    Add a LICENSE file to clarify usage rights

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., LICENSE.md) in the root of the repository. The content should specify the chosen license (e.g., MIT, Apache-2.0, or a Creative Commons license like CC-BY-4.0 for the paper content itself).
  • mediumhomepage#3
    Add the arXiv paper link as the repository homepage

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2402.17177

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 lichao-sun/SoraReview
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Vision Transformer (ViT)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Vision Transformer (ViT) · recommended 1×
  2. Swin Transformer · recommended 1×
  3. DeiT (Data-efficient Image Transformers) · recommended 1×
  4. ResNet (Residual Networks) · recommended 1×
  5. EfficientNet · recommended 1×
  • CATEGORY QUERY
    What are the core technologies and limitations of large vision models currently available?
    you: not recommended
    AI recommended (in order):
    1. Vision Transformer (ViT)
    2. Swin Transformer
    3. DeiT (Data-efficient Image Transformers)
    4. ResNet (Residual Networks)
    5. EfficientNet
    6. ConvNeXt
    7. DINO (Self-distillation with no labels)
    8. MAE (Masked Autoencoders)
    9. SimCLR
    10. BYOL (Bootstrap Your Own Latent)
    11. DALL-E 2
    12. Stable Diffusion
    13. Midjourney
    14. Imagen
    15. CLIP (Contrastive Language-Image Pre-training)
    16. BLIP (Bootstrapping Language-Image Pre-training)
    17. Flamingo

    AI recommended 17 alternatives but never named lichao-sun/SoraReview. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a comprehensive review of advancements and opportunities in generative video AI.
    you: not recommended
    AI recommended (in order):
    1. RunwayML Gen-2
    2. Pika Labs
    3. Stability AI's Stable Video Diffusion (SVD)
    4. Google's Lumiere
    5. AnimateDiff (guoyww/AnimateDiff)
    6. Meta's Make-A-Video
    7. Google's Phenaki

    AI recommended 7 alternatives but never named lichao-sun/SoraReview. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 lichao-sun/SoraReview?
    pass
    AI named lichao-sun/SoraReview explicitly

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

  • If a team adopts lichao-sun/SoraReview in production, what risks or prerequisites should they evaluate first?
    pass
    AI named lichao-sun/SoraReview 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 lichao-sun/SoraReview solve, and who is the primary audience?
    pass
    AI named lichao-sun/SoraReview 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 lichao-sun/SoraReview. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/lichao-sun/SoraReview.svg)](https://repogeo.com/en/r/lichao-sun/SoraReview)
HTML
<a href="https://repogeo.com/en/r/lichao-sun/SoraReview"><img src="https://repogeo.com/badge/lichao-sun/SoraReview.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

lichao-sun/SoraReview — 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