RRepoGEO

REPOGEO REPORT · LITE

manycore-research/SpatialLM

Default branch main · commit 029808be · scanned 5/19/2026, 1:02:23 AM

GitHub: 4,555 stars · 378 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)

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

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 manycore-research/SpatialLM, 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
    Reposition the README's main heading to clarify project domain

    Why:

    CURRENT
    # SpatialLM
    COPY-PASTE FIX
    # SpatialLM: Training Large Language Models for Structured Indoor Modeling
  • mediumtopics#2
    Expand repository topics for better category matching

    Why:

    CURRENT
    mllm, point-clouds, scene-understanding, spatial-intelligence
    COPY-PASTE FIX
    mllm, multimodal-llm, point-clouds, 3d-scene-understanding, scene-understanding, spatial-intelligence, indoor-modeling, spatial-reasoning
  • lowlicense#3
    Add a clear license statement to the README

    Why:

    COPY-PASTE FIX
    Add a section (e.g., "## License") to the README stating which license(s) apply to the project and referencing the LICENSE file for full details.

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 manycore-research/SpatialLM
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4 / GPT-3.5 Turbo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4 / GPT-3.5 Turbo · recommended 1×
  2. Google PaLM 2 / Gemini · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. openai/CLIP · recommended 1×
  5. YOLO / Mask R-CNN · recommended 1×
  • CATEGORY QUERY
    How to train large language models for understanding structured indoor environments?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5 Turbo
    2. Google PaLM 2 / Gemini
    3. Hugging Face Transformers (huggingface/transformers)
    4. CLIP (openai/CLIP)
    5. YOLO / Mask R-CNN
    6. Habitat (facebookresearch/habitat-lab)
    7. Robotics Operating System (ROS)

    AI recommended 7 alternatives but never named manycore-research/SpatialLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What MLLM frameworks specialize in 3D scene understanding and spatial reasoning from point clouds?
    you: not recommended
    AI recommended (in order):
    1. OpenScene
    2. PointCLIP / PointCLIP V2
    3. ULIP
    4. Point-BERT
    5. 3D-LLM
    6. MinkowskiEngine

    AI recommended 6 alternatives but never named manycore-research/SpatialLM. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 manycore-research/SpatialLM?
    pass
    AI named manycore-research/SpatialLM explicitly

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

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

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

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manycore-research/SpatialLM — 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