RRepoGEO

REPOGEO REPORT · LITE

ShareGPT4Omni/ShareGPT4Video

Default branch master · commit 7e02ee61 · scanned 7/1/2026, 6:53:15 PM

GitHub: 1,092 stars · 46 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 ShareGPT4Omni/ShareGPT4Video, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root, specifying the chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0) to ensure legal clarity and encourage adoption.
  • highreadme#2
    Reposition the README's opening paragraph to clarify its research focus

    Why:

    CURRENT
    🚀🚀🚀 Official implementation of **ShareGPT4Video: Improving Video Understanding and Generation with Better Captions**.
    COPY-PASTE FIX
    🚀🚀🚀 This is the official research implementation of **ShareGPT4Video**, a NeurIPS 2024 project that introduces a novel large video-language model and dataset for **improving video understanding and generation with better, highly descriptive captions**.
  • mediumabout#3
    Expand the repository description to highlight the dataset and model

    Why:

    CURRENT
    [NeurIPS 2024] An official implementation of "ShareGPT4Video: Improving Video Understanding and Generation with Better Captions"
    COPY-PASTE FIX
    [NeurIPS 2024] Official implementation of ShareGPT4Video: a large video-language model and dataset for improving video understanding and generation with better captions.

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 ShareGPT4Omni/ShareGPT4Video
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Video Intelligence API
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Video Intelligence API · recommended 2×
  2. huggingface/transformers · recommended 2×
  3. DeepMind's Perceiver IO · recommended 2×
  4. Azure Video Indexer · recommended 1×
  5. OpenAI's GPT-4o · recommended 1×
  • CATEGORY QUERY
    How can I generate highly descriptive video captions to improve video understanding and generation?
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Video Intelligence API
    2. Azure Video Indexer
    3. OpenAI's GPT-4o
    4. Meta's VideoMAE (facebookresearch/VideoMAE)
    5. Hugging Face Transformers (huggingface/transformers)
    6. DeepMind's Perceiver IO

    AI recommended 6 alternatives but never named ShareGPT4Omni/ShareGPT4Video. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help create better video captions using large multimodal models for text-to-video tasks?
    you: not recommended
    AI recommended (in order):
    1. DeepMind's Perceiver IO
    2. Flamingo
    3. OpenAI's GPT-4V (Vision)
    4. Google Cloud Video Intelligence API
    5. Hugging Face Transformers Library (huggingface/transformers)
    6. BLIP (Bootstrapping Language-Image Pre-training)
    7. ViLT (Vision-and-Language Transformer)
    8. OFA (One-For-All)
    9. Microsoft Azure Video Indexer
    10. AssemblyAI

    AI recommended 10 alternatives but never named ShareGPT4Omni/ShareGPT4Video. 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 ShareGPT4Omni/ShareGPT4Video?
    pass
    AI named ShareGPT4Omni/ShareGPT4Video explicitly

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

  • If a team adopts ShareGPT4Omni/ShareGPT4Video in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ShareGPT4Omni/ShareGPT4Video 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 ShareGPT4Omni/ShareGPT4Video solve, and who is the primary audience?
    pass
    AI did not name ShareGPT4Omni/ShareGPT4Video — 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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MARKDOWN (README)
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ShareGPT4Omni/ShareGPT4Video — 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