RRepoGEO

REPOGEO REPORT · LITE

opendatalab/WanJuan1.0

Default branch main · commit 17269a7d · scanned 5/29/2026, 8:22:55 PM

GitHub: 574 stars · 28 forks

AI VISIBILITY SCORE
35 /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
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 opendatalab/WanJuan1.0, 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 for better categorization

    Why:

    COPY-PASTE FIX
    multimodal-dataset, chinese-ai, large-language-models, computer-vision, natural-language-processing, dataset, ai-data
  • highreadme#2
    Emphasize 'Chinese' in the README's opening description

    Why:

    CURRENT
    Intern · WanJuan 1.0 is the first open-source version of Intern · Wanjuan multimodal corpus, which includes three parts: text dataset, image-text dataset, and video dataset, with a total data volume exceeding 2TB.
    COPY-PASTE FIX
    Intern · WanJuan 1.0 is the first open-source version of Intern · Wanjuan, a large-scale, high-quality Chinese multimodal corpus. It includes three parts: text dataset, image-text dataset, and video dataset, with a total data volume exceeding 2TB.
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    [Insert official project homepage URL here, e.g., https://opendatalab.org/WanJuan1.0]

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 opendatalab/WanJuan1.0
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LAION-5B
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LAION-5B · recommended 2×
  2. Conceptual Captions · recommended 2×
  3. COCO · recommended 1×
  4. Visual Genome · recommended 1×
  5. Flickr30k · recommended 1×
  • CATEGORY QUERY
    Where can I find a large, pre-processed multimodal dataset for training advanced AI models?
    you: not recommended
    AI recommended (in order):
    1. LAION-5B
    2. Conceptual Captions
    3. COCO
    4. Visual Genome
    5. Flickr30k
    6. Kinetics
    7. AudioSet

    AI recommended 7 alternatives but never named opendatalab/WanJuan1.0. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a comprehensive, integrated text, image, and video dataset for general AI model development.
    you: not recommended
    AI recommended (in order):
    1. LAION-5B
    2. WebVid-10M
    3. WebVid-2.5M
    4. Conceptual Captions
    5. Kinetics-700
    6. Kinetics-600
    7. Kinetics-400
    8. ActivityNet Captions
    9. MSR-VTT

    AI recommended 9 alternatives but never named opendatalab/WanJuan1.0. 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 opendatalab/WanJuan1.0?
    pass
    AI named opendatalab/WanJuan1.0 explicitly

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

  • If a team adopts opendatalab/WanJuan1.0 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named opendatalab/WanJuan1.0 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 opendatalab/WanJuan1.0 solve, and who is the primary audience?
    pass
    AI named opendatalab/WanJuan1.0 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 opendatalab/WanJuan1.0. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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opendatalab/WanJuan1.0 — 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