RRepoGEO

REPOGEO REPORT · LITE

IBM/Dromedary

Default branch main · commit 0b86740e · scanned 6/19/2026, 9:43:08 PM

GitHub: 1,138 stars · 88 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
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 IBM/Dromedary, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    llm, large-language-models, self-alignment, ai-alignment, neurips, machine-learning, deep-learning, nlp, foundation-models
  • highreadme#2
    Reposition the core purpose statement immediately after the main title in the README

    Why:

    CURRENT
    <div align="center">
    
    </div>
    
    <div align="center">
    
    ### NeurIPS 2023 (Spotlight)
    
    ## Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision
    
    </div>
    COPY-PASTE FIX
    <div align="center">
    
    </div>
    
    <div align="center">
    
    ### NeurIPS 2023 (Spotlight)
    
    ## Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision
    
    Dromedary is an open-source self-aligned language model trained with minimal human supervision, focused on creating helpful, ethical, and reliable LLMs.
    
    </div>
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://ibm.github.io/Dromedary/

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 IBM/Dromedary
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/trl
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/trl · recommended 1×
  2. microsoft/DeepSpeed · recommended 1×
  3. OpenAI's API · recommended 1×
  4. GPT-4 · recommended 1×
  5. facebookresearch/llama · recommended 1×
  • CATEGORY QUERY
    How to self-align a large language model from scratch with minimal human oversight?
    you: not recommended
    AI recommended (in order):
    1. TRL (huggingface/trl)
    2. DeepSpeed-Chat (microsoft/DeepSpeed)
    3. OpenAI's API
    4. GPT-4
    5. Llama-2-Chat (facebookresearch/llama)
    6. Anthropic's Claude
    7. LangChain (langchain-ai/langchain)
    8. LlamaIndex (run-llama/llama_index)
    9. Hugging Face Transformers (huggingface/transformers)
    10. DeepMind's AlphaCode
    11. TextAttack (QData/TextAttack)
    12. NLPAug (makcedward/nlpaug)
    13. PyTorch (pytorch/pytorch)
    14. TensorFlow (tensorflow/tensorflow)
    15. The Pile
    16. C4

    AI recommended 16 alternatives but never named IBM/Dromedary. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source projects help create more helpful and ethical LLMs efficiently?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. Hugging Face Datasets
    3. OpenAssistant Conversations Dataset (OASST1)
    4. LAION-AI Open-Assistant
    5. trl
    6. DeepSpeed
    7. Accelerate
    8. LM-Harness (EleutherAI/lm-evaluation-harness)
    9. Finetune.ai

    AI recommended 9 alternatives but never named IBM/Dromedary. 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 IBM/Dromedary?
    pass
    AI named IBM/Dromedary explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite