RRepoGEO

REPOGEO REPORT · LITE

WangRongsheng/ChatGenTitle

Default branch main · commit 799c25ca · scanned 6/1/2026, 5:01:56 PM

GitHub: 837 stars · 70 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 WangRongsheng/ChatGenTitle, 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
    Add a concise English positioning statement to the README's opening

    Why:

    COPY-PASTE FIX
    ChatGenTitle is an AI-powered tool designed to generate high-quality titles for research papers, fine-tuned on millions of arXiv paper abstracts using LLaMA models.
  • mediumhomepage#2
    Add the online demo link as the repository homepage

    Why:

    COPY-PASTE FIX
    https://drive.google.com/file/d/1akrC4-YnYdiyD1_VK-92hncN7HS0FLf5/view?usp=sharing
  • lowlicense#3
    Clarify the project's license(s) in the README

    Why:

    COPY-PASTE FIX
    This project is licensed under [Specify License Name(s) and terms, e.g., 'a custom license as detailed in the LICENSE file.']. Please refer to 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 WangRongsheng/ChatGenTitle
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. OpenAI API · recommended 1×
  3. ChatGPT · recommended 1×
  4. Google Gemini (Pro/Ultra) · recommended 1×
  5. Google AI Studio · recommended 1×
  • CATEGORY QUERY
    How can I use large language models to generate titles for my research papers?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5 Turbo
    2. OpenAI API
    3. ChatGPT
    4. Google Gemini (Pro/Ultra)
    5. Google AI Studio
    6. Google Cloud Vertex AI
    7. Anthropic Claude 3 (Opus/Sonnet/Haiku)
    8. Anthropic API
    9. Claude.ai
    10. Meta Llama 3 (8B/70B)
    11. Hugging Face
    12. Replicate
    13. Together AI
    14. Hugging Face Transformers (huggingface/transformers)
    15. T5
    16. BART
    17. BERT
    18. Hugging Face Hub

    AI recommended 18 alternatives but never named WangRongsheng/ChatGenTitle. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help fine-tune open-source LLMs for scientific document title generation?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch Lightning
    3. DeepSpeed
    4. Hugging Face PEFT library
    5. Weights & Biases
    6. Optuna

    AI recommended 6 alternatives but never named WangRongsheng/ChatGenTitle. 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 WangRongsheng/ChatGenTitle?
    pass
    AI named WangRongsheng/ChatGenTitle explicitly

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

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

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MARKDOWN (README)
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HTML
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WangRongsheng/ChatGenTitle — 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