RRepoGEO

REPOGEO REPORT · LITE

MME-Benchmarks/Video-MME

Default branch main · commit 06c2315b · scanned 6/14/2026, 7:02:31 AM

GitHub: 779 stars · 30 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 MME-Benchmarks/Video-MME, 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
  • highreadme#1
    Explicitly differentiate the repo as an evaluation benchmark, not a model

    Why:

    COPY-PASTE FIX
    Add a sentence early in the README, perhaps right after the main title, explicitly stating: "Video-MME is a comprehensive *evaluation benchmark* for Multi-modal LLMs in video analysis, *not* a deployable model or system itself."
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root, for example, using the MIT License text.
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    Set the repository homepage to `https://video-mme.github.io/` (or the actual project page URL).

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 MME-Benchmarks/Video-MME
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google's Gemini
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google's Gemini · recommended 1×
  2. OpenAI's GPT-4V (GPT-4 with Vision) · recommended 1×
  3. facebookresearch/VideoMAE · recommended 1×
  4. microsoft/Florence-2 · recommended 1×
  5. Google's PaLM-E · recommended 1×
  • CATEGORY QUERY
    How can I assess the video analysis capabilities of multi-modal large language models?
    you: not recommended
    AI recommended (in order):
    1. Google's Gemini
    2. OpenAI's GPT-4V (GPT-4 with Vision)
    3. Meta's VideoMAE / VideoMAE V2 (facebookresearch/VideoMAE)
    4. Microsoft's Florence-2 (microsoft/Florence-2)
    5. Google's PaLM-E
    6. LLaVA-1.5 (haotian-liu/LLaVA)
    7. InstructBLIP (salesforce/LAVIS)
    8. InternVideo2 (OpenGVLab/InternVideo2)

    AI recommended 8 alternatives but never named MME-Benchmarks/Video-MME. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best benchmarks for evaluating video understanding in large vision models?
    you: not recommended
    AI recommended (in order):
    1. Kinetics
    2. Something-Something V2
    3. Moments in Time (MiT)
    4. ActivityNet (v1.3)
    5. THUMOS14
    6. MSR-VTT (Microsoft Research Video to Text)
    7. TVQA

    AI recommended 7 alternatives but never named MME-Benchmarks/Video-MME. 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 MME-Benchmarks/Video-MME?
    pass
    AI named MME-Benchmarks/Video-MME explicitly

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

  • If a team adopts MME-Benchmarks/Video-MME in production, what risks or prerequisites should they evaluate first?
    pass
    AI named MME-Benchmarks/Video-MME 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 MME-Benchmarks/Video-MME solve, and who is the primary audience?
    pass
    AI named MME-Benchmarks/Video-MME 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 MME-Benchmarks/Video-MME. 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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MME-Benchmarks/Video-MME — 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