REPOGEO REPORT · LITE
DAMO-NLP-SG/VideoLLaMA2
Default branch main · commit c0bb03ab · scanned 5/15/2026, 6:57:44 PM
GitHub: 1,297 stars · 88 forks
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.
- hightopics#1Add relevant topics to the repository
Why:
COPY-PASTE FIXvideo-llm, multimodal-llm, spatial-temporal-modeling, audio-understanding, video-comprehension, deep-learning, computer-vision, nlp
- highreadme#2Add a concise, high-level summary statement at the very top of the README
Why:
COPY-PASTE FIXVideoLLaMA 2 is an advanced large language model designed for comprehensive video understanding, integrating spatial-temporal modeling and audio analysis to interpret long, unconstrained video content. It enables AI researchers and developers to build models that reason about both visual and auditory information in videos.
- mediumhomepage#3Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIXhttps://arxiv.org/abs/2406.07476 (or a dedicated project page if one exists)
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.
- MMAction2 · recommended 2×
- PyTorch · recommended 1×
- torchvision · recommended 1×
- torchaudio · recommended 1×
- TensorFlow · recommended 1×
- CATEGORY QUERYHow can I build an AI model that understands both video content and accompanying audio?you: not recommendedAI recommended (in order):
- PyTorch
- torchvision
- torchaudio
- TensorFlow
- Keras
- TensorFlow Hub
- Hugging Face Transformers
- VideoMAE
- BEiT
- Wav2Vec2
- MMAction2
- DeepMind's Perceiver IO
AI recommended 12 alternatives but never named DAMO-NLP-SG/VideoLLaMA2. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat are the best tools for advanced spatial-temporal reasoning and video comprehension?you: not recommendedAI recommended (in order):
- PyTorchVideo
- MMAction2
AI recommended 2 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 completenesswarn
Suggestion:
- README presencepass
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?passAI 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?passAI 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?passAI 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?
Embed your GEO score
Drop this badge into the README of DAMO-NLP-SG/VideoLLaMA2. 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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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