RRepoGEO

REPOGEO REPORT · LITE

uber-research/PPLM

Default branch master · commit e236b898 · scanned 5/28/2026, 10:53:11 PM

GitHub: 1,154 stars · 204 forks

AI VISIBILITY SCORE
53 /100
Needs work
Category recall
1 / 2
Avg rank #10.0 when recommended
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 uber-research/PPLM, 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 README H1 to clarify PPLM is a *method* for controlled generation

    Why:

    CURRENT
    This repository contains code to run the Plug and Play Language Model (PPLM), as described in this **blog post** and **arXiv paper**.
    COPY-PASTE FIX
    PPLM (Plug and Play Language Model) is an implementation of a novel method for **controlled text generation**. It allows users to steer the topic and attributes of large language models (like GPT-2) *without requiring any fine-tuning or retraining*. This repository contains the official code, as described in our **blog post** and **arXiv paper**.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/1912.02164
  • lowtopics#3
    Add more specific topics related to controlled text generation

    Why:

    CURRENT
    deep-learning, language-modeling, machine-learning, natural-language-generation, natural-language-processing, nlp
    COPY-PASTE FIX
    deep-learning, language-modeling, machine-learning, natural-language-generation, natural-language-processing, nlp, controlled-text-generation, llm-steering, text-steering, generative-ai-methods

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
1 / 2
50% of queries surface uber-research/PPLM
Avg rank
#10.0
Lower is better. #1 = top recommendation.
Share of voice
3%
Of all named tools, what % are you?
Top rival
Anthropic Claude 3
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Anthropic Claude 3 · recommended 2×
  2. OpenAI Fine-tuning API · recommended 2×
  3. OpenAI GPT-4 · recommended 1×
  4. Google Gemini · recommended 1×
  5. Meta Llama 3 · recommended 1×
  • CATEGORY QUERY
    How to guide large language model output towards specific topics or styles without retraining?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4
    2. Anthropic Claude 3
    3. Google Gemini
    4. Meta Llama 3
    5. OpenAI GPT-4o
    6. Anthropic Claude 3
    7. Google Gemini 1.5 Pro
    8. LangChain
    9. LlamaIndex
    10. Pinecone
    11. Weaviate
    12. ChromaDB
    13. Python's `re` module
    14. NLTK
    15. spaCy
    16. Guidance
    17. LMQL
    18. Hugging Face PEFT library
    19. OpenAI Fine-tuning API
    20. Google Cloud Vertex AI
    21. NVIDIA NeMo Guardrails
    22. OpenAI Moderation API

    AI recommended 22 alternatives but never named uber-research/PPLM. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking methods to influence generated text attributes like sentiment or domain with pre-trained models.
    you: #10
    AI recommended (in order):
    1. OpenAI API
    2. Anthropic Claude
    3. Google Gemini API
    4. Hugging Face Transformers
    5. BERT
    6. RoBERTa
    7. GPT-2
    8. T5
    9. OpenAI Fine-tuning API
    10. PPLM ← you
    11. CTRL
    12. GLTR
    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 uber-research/PPLM?
    pass
    AI named uber-research/PPLM explicitly

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

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

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

Embed your GEO score

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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite