RRepoGEO

REPOGEO REPORT · LITE

thu-ml/RDT2

Default branch main · commit 0797b4c6 · scanned 5/28/2026, 7:37:50 AM

GitHub: 772 stars · 51 forks

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 thu-ml/RDT2, 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
  • highabout#1
    Update the repository description for clarity

    Why:

    CURRENT
    Official code of RDT 2
    COPY-PASTE FIX
    Official code for RDT2, a robotics diffusion transformer enabling zero-shot cross-embodiment generalization by scaling up UMI data.
  • mediumhomepage#2
    Add the project's official homepage URL

    Why:

    COPY-PASTE FIX
    https://rdt-robotics.github.io/rdt2/

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 thu-ml/RDT2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RT-1
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. RT-1 · recommended 1×
  2. RT-2 · recommended 1×
  3. RT-X · recommended 1×
  4. CLIP · recommended 1×
  5. OWL-ViT · recommended 1×
  • CATEGORY QUERY
    How can I achieve zero-shot generalization for robotics across different hardware platforms?
    you: not recommended
    AI recommended (in order):
    1. RT-1
    2. RT-2
    3. RT-X
    4. CLIP
    5. OWL-ViT
    6. Grounded-SAM
    7. Diffusion Policy
    8. MAML
    9. Reptile
    10. NVIDIA Isaac Sim
    11. MuJoCo
    12. Gazebo
    13. Robosuite
    14. Habitat
    15. RoboStack

    AI recommended 15 alternatives but never named thu-ml/RDT2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a robotics framework that supports large-scale pre-trained diffusion models for control.
    you: not recommended
    AI recommended (in order):
    1. ROS 2
    2. PyTorch
    3. TensorFlow
    4. ros2_control
    5. Isaac Sim
    6. NVIDIA Omniverse
    7. Isaac SDK
    8. RLlib
    9. Ray
    10. OpenVINO
    11. Mojo

    AI recommended 11 alternatives but never named thu-ml/RDT2. 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 thu-ml/RDT2?
    pass
    AI named thu-ml/RDT2 explicitly

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

  • If a team adopts thu-ml/RDT2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named thu-ml/RDT2 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 thu-ml/RDT2 solve, and who is the primary audience?
    pass
    AI named thu-ml/RDT2 explicitly

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

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thu-ml/RDT2 — 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