RRepoGEO

REPOGEO REPORT · LITE

mit-han-lab/streaming-vlm

Default branch main · commit a940d8cb · scanned 6/4/2026, 1:47:56 PM

GitHub: 1,002 stars · 62 forks

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 mit-han-lab/streaming-vlm, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify the project's unique positioning in the README's opening

    Why:

    CURRENT
    # StreamingVLM: Real-Time Understanding for Infinite Video Streams
    COPY-PASTE FIX
    # StreamingVLM: An Open-Source Vision-Language Model for Real-Time Understanding of Infinite Video Streams
  • mediumhomepage#2
    Add the demo page URL to the repository homepage field

    Why:

    COPY-PASTE FIX
    https://streamingvlm.hanlab.ai

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 mit-han-lab/streaming-vlm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenVINO Toolkit
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenVINO Toolkit · recommended 1×
  2. NVIDIA TensorRT · recommended 1×
  3. ONNX Runtime · recommended 1×
  4. DeepStream SDK · recommended 1×
  5. Hugging Face Transformers Library · recommended 1×
  • CATEGORY QUERY
    How to achieve real-time vision-language understanding for continuous video streams efficiently?
    you: not recommended
    AI recommended (in order):
    1. OpenVINO Toolkit
    2. NVIDIA TensorRT
    3. ONNX Runtime
    4. DeepStream SDK
    5. Hugging Face Transformers Library
    6. PyTorch
    7. TensorFlow
    8. Triton Inference Server
    9. MediaPipe
    10. TensorFlow Lite

    AI recommended 10 alternatives but never named mit-han-lab/streaming-vlm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a robust VLM solution for analyzing extremely long video content without performance degradation.
    you: not recommended
    AI recommended (in order):
    1. Google Cloud Video AI API
    2. AWS Rekognition Video
    3. Azure Video Analyzer
    4. OpenAI's GPT-4o
    5. FFmpeg
    6. PyAV (PyAV/PyAV)
    7. Whisper (openai/whisper)
    8. Kinetica
    9. Clarifai
    10. VGGish
    11. YOLOv8 (ultralytics/ultralytics)
    12. DETR (facebookresearch/detr)
    13. SAM (facebookresearch/segment-anything)
    14. Apache Spark (apache/spark)
    15. Kubernetes (kubernetes/kubernetes)

    AI recommended 15 alternatives but never named mit-han-lab/streaming-vlm. 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 mit-han-lab/streaming-vlm?
    pass
    AI did not name mit-han-lab/streaming-vlm — 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?

  • If a team adopts mit-han-lab/streaming-vlm in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mit-han-lab/streaming-vlm 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 mit-han-lab/streaming-vlm solve, and who is the primary audience?
    pass
    AI named mit-han-lab/streaming-vlm explicitly

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

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mit-han-lab/streaming-vlm — 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