RRepoGEO

REPOGEO REPORT · LITE

OpenSenseNova/SenseNova-U1

Default branch main · commit fd26e6db · scanned 6/6/2026, 9:52:39 PM

GitHub: 2,721 stars · 257 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 OpenSenseNova/SenseNova-U1, 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
    Add a clear introductory sentence to the README

    Why:

    CURRENT
    # SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

<p align="center">
  <strong>English</strong> | <a href="./README_CN.md">简体中文</a>
</p>
    COPY-PASTE FIX
    # SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

SenseNova-U1 is a cutting-edge multimodal AI model and framework designed for unified understanding and generation across vision, language, and audio.

<p align="center">
  <strong>English</strong> | <a href="./README_CN.md">简体中文</a>
</p>
  • mediumabout#2
    Update the repository description for clarity

    Why:

    CURRENT
    SenseNova-U series: Native Unified Paradigm with NEO-unify from the First Principles
    COPY-PASTE FIX
    SenseNova-U1 is a multimodal AI model and framework for unified understanding and generation across vision, language, and audio.

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 OpenSenseNova/SenseNova-U1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 1×
  2. huggingface/diffusers · recommended 1×
  3. tensorflow/tensorflow · recommended 1×
  4. keras-team/keras · recommended 1×
  5. google/mediapipe · recommended 1×
  • CATEGORY QUERY
    Looking for a unified AI framework for both understanding and generating multimodal content.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. Diffusers (huggingface/diffusers)
    3. TensorFlow (tensorflow/tensorflow)
    4. Keras (keras-team/keras)
    5. MediaPipe (google/mediapipe)
    6. PyTorch (pytorch/pytorch)
    7. PyTorch Lightning (Lightning-AI/lightning)
    8. TorchVision (pytorch/vision)
    9. TorchAudio (pytorch/audio)
    10. OpenAI API
    11. GPT-4V
    12. DALL-E 3
    13. Whisper
    14. Fairseq (facebookresearch/fairseq)
    15. JAX (google/jax)
    16. Flax (google/flax)
    17. Haiku (deepmind/dm-haiku)

    AI recommended 17 alternatives but never named OpenSenseNova/SenseNova-U1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are efficient multimodal models for generation, especially on systems with limited VRAM?
    you: not recommended
    AI recommended (in order):
    1. LLaVA
    2. MiniGPT-4 / MiniGPT-v2
    3. BLIP-2
    4. InstructBLIP
    5. Fuyu-8B
    6. Qwen-VL
    7. BakLLaVA

    AI recommended 7 alternatives but never named OpenSenseNova/SenseNova-U1. 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 OpenSenseNova/SenseNova-U1?
    pass
    AI named OpenSenseNova/SenseNova-U1 explicitly

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

  • If a team adopts OpenSenseNova/SenseNova-U1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named OpenSenseNova/SenseNova-U1 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 OpenSenseNova/SenseNova-U1 solve, and who is the primary audience?
    pass
    AI named OpenSenseNova/SenseNova-U1 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 OpenSenseNova/SenseNova-U1. 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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OpenSenseNova/SenseNova-U1 — 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