RRepoGEO

REPOGEO REPORT · LITE

TideDra/lmm-r1

Default branch main · commit f917f186 · scanned 6/12/2026, 7:51:44 PM

GitHub: 844 stars · 53 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 TideDra/lmm-r1, 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
  • mediumreadme#1
    Add a clear, concise first sentence to the Introduction section

    Why:

    CURRENT
    Smaller 3B Large Multimodal Models (LMMs) struggle with reasoning tasks due to their limited parameter capacity and the inherent complexity of integrating visual perception with logical reasoning.
    COPY-PASTE FIX
    LMM-R1 extends OpenRLHF to support Reinforcement Learning (RL) training for Large Multimodal Models (LMMs), specifically designed to reproduce DeepSeek-R1's strong reasoning abilities on multimodal tasks. Smaller 3B Large Multimodal Models (LMMs) struggle with reasoning tasks due to their limited parameter capacity and the inherent complexity of integrating visual perception with logical reasoning.
  • lowhomepage#2
    Add the project page URL to the repository homepage metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://forjadeforest.github.io/LMM-R1-ProjectPage/

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 TideDra/lmm-r1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ray-project/ray
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ray-project/ray · recommended 2×
  2. Hugging Face Transformers · recommended 1×
  3. TRL · recommended 1×
  4. ViT-GPT2 · recommended 1×
  5. BLIP · recommended 1×
  • CATEGORY QUERY
    How can I train multimodal large language models using reinforcement learning techniques effectively?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. TRL
    3. ViT-GPT2
    4. BLIP
    5. LLaVA
    6. InstructBLIP
    7. Qwen-VL
    8. Accelerate
    9. DeepMind's Acme
    10. TensorFlow
    11. PyTorch
    12. Meta's Habitat Lab
    13. Google's Dopamine
    14. Keras
    15. RLlib
    16. Ray
    17. OpenAI Gym/Farama Foundation Gymnasium

    AI recommended 17 alternatives but never named TideDra/lmm-r1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools help improve reasoning abilities in 3B LMMs through reinforcement learning?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. Accelerate (huggingface/accelerate)
    3. Hugging Face TRL (huggingface/trl)
    4. DeepSpeed (microsoft/DeepSpeed)
    5. FSDP (pytorch/pytorch)
    6. RLlib (ray-project/ray)
    7. Ray (ray-project/ray)
    8. Gymnasium (Farama-Foundation/Gymnasium)

    AI recommended 8 alternatives but never named TideDra/lmm-r1. 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 TideDra/lmm-r1?
    pass
    AI named TideDra/lmm-r1 explicitly

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

  • If a team adopts TideDra/lmm-r1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named TideDra/lmm-r1 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 TideDra/lmm-r1 solve, and who is the primary audience?
    pass
    AI named TideDra/lmm-r1 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 TideDra/lmm-r1. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/TideDra/lmm-r1.svg)](https://repogeo.com/en/r/TideDra/lmm-r1)
HTML
<a href="https://repogeo.com/en/r/TideDra/lmm-r1"><img src="https://repogeo.com/badge/TideDra/lmm-r1.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

TideDra/lmm-r1 — 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