RRepoGEO

REPOGEO REPORT · LITE

DAMO-NLP-SG/VideoLLaMA2

Default branch main · commit c0bb03ab · scanned 6/26/2026, 1:27:53 PM

GitHub: 1,302 stars · 89 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 DAMO-NLP-SG/VideoLLaMA2, 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 improve categorization

    Why:

    COPY-PASTE FIX
    video-llm, multimodal-ai, video-understanding, audio-understanding, large-language-models, deep-learning, pytorch
  • highreadme#2
    Add a concise positioning statement to the README's opening

    Why:

    CURRENT
    <h3 align="center"><a href="https://arxiv.org/abs/2406.07476" style="color:#9C276A">
VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs</a></h3>
    COPY-PASTE FIX
    This repository presents VideoLLaMA 2, a state-of-the-art large language model designed for comprehensive video understanding, integrating advanced spatial-temporal modeling and audio analysis.

<h3 align="center"><a href="https://arxiv.org/abs/2406.07476" style="color:#9C276A">
VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs</a></h3>
  • mediumhomepage#3
    Add a homepage link to the project's Hugging Face space

    Why:

    COPY-PASTE FIX
    https://huggingface.co/spaces/lixin4ever/VideoLLaMA2

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 DAMO-NLP-SG/VideoLLaMA2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch · recommended 2×
  2. TensorFlow · recommended 2×
  3. MMAction2 · recommended 2×
  4. OpenCV · recommended 2×
  5. Librosa · recommended 2×
  • CATEGORY QUERY
    How can I build AI models that comprehend video content, including visual and audio elements?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. TensorFlow
    3. MMAction2
    4. Keras
    5. OpenCV
    6. Librosa

    AI recommended 6 alternatives but never named DAMO-NLP-SG/VideoLLaMA2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a library to perform multimodal analysis on videos, focusing on temporal dynamics and sound.
    you: not recommended
    AI recommended (in order):
    1. PyTorchVideo
    2. MMAction2
    3. Keras-Video-Classifier
    4. DeepMind's Perceiver IO
    5. Librosa
    6. OpenCV
    7. PyTorch
    8. TensorFlow

    AI recommended 8 alternatives but never named DAMO-NLP-SG/VideoLLaMA2. 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 DAMO-NLP-SG/VideoLLaMA2?
    pass
    AI named DAMO-NLP-SG/VideoLLaMA2 explicitly

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

  • If a team adopts DAMO-NLP-SG/VideoLLaMA2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named DAMO-NLP-SG/VideoLLaMA2 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 DAMO-NLP-SG/VideoLLaMA2 solve, and who is the primary audience?
    pass
    AI named DAMO-NLP-SG/VideoLLaMA2 explicitly

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

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DAMO-NLP-SG/VideoLLaMA2 — 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