RRepoGEO

REPOGEO REPORT · LITE

ymcui/Chinese-XLNet

Default branch master · commit 4386834e · scanned 5/9/2026, 10:47:19 PM

GitHub: 1,649 stars · 279 forks

AI VISIBILITY SCORE
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 ymcui/Chinese-XLNet, 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's opening to highlight competitive advantage

    Why:

    CURRENT
    本项目提供了面向中文的XLNet预训练模型,旨在丰富中文自然语言处理资源,提供多元化的中文预训练模型选择。
    COPY-PASTE FIX
    本项目提供高性能的中文XLNet预训练模型,是中文自然语言处理领域中BERT、RoBERTa和ERNIE等模型的强大替代方案,尤其适用于需要高级语言理解的任务。
  • mediumtopics#2
    Add more specific topics for pre-trained models and Chinese NLP

    Why:

    CURRENT
    natural-language-processing, nlp, pytorch, tensorflow, xlnet
    COPY-PASTE FIX
    natural-language-processing, nlp, pytorch, tensorflow, xlnet, pre-trained-models, transformer-models, chinese-nlp
  • lowreadme#3
    Add a brief comparison or unique selling proposition for XLNet

    Why:

    COPY-PASTE FIX
    在README的介绍部分或单独的'特性'/'优势'部分,增加一句话或一段话,例如:'与传统的BERT类模型不同,中文XLNet采用置换语言模型训练目标,能够更有效地捕捉双向上下文信息,在多项中文NLP基准测试中展现出卓越性能。'

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 ymcui/Chinese-XLNet
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
BERT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. BERT · recommended 2×
  2. RoBERTa · recommended 2×
  3. ERNIE · recommended 2×
  4. MacBERT · recommended 2×
  5. XLNet · recommended 2×
  • CATEGORY QUERY
    I need robust pre-trained language models to enhance performance on Chinese NLP applications.
    you: not recommended
    AI recommended (in order):
    1. BERT
    2. RoBERTa
    3. ERNIE
    4. MacBERT
    5. XLNet
    6. mT5
    7. CPM

    AI recommended 7 alternatives but never named ymcui/Chinese-XLNet. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective transformer-based models for processing Chinese text, compatible with PyTorch or TensorFlow?
    you: not recommended
    AI recommended (in order):
    1. BERT
    2. RoBERTa
    3. ERNIE
    4. MacBERT
    5. ELECTRA
    6. XLNet
    7. Hugging Face Transformers library

    AI recommended 7 alternatives but never named ymcui/Chinese-XLNet. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 ymcui/Chinese-XLNet?
    pass
    AI did not name ymcui/Chinese-XLNet — likely talking about a different project

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

  • If a team adopts ymcui/Chinese-XLNet in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ymcui/Chinese-XLNet 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 ymcui/Chinese-XLNet solve, and who is the primary audience?
    pass
    AI did not name ymcui/Chinese-XLNet — likely talking about a different project

    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 ymcui/Chinese-XLNet. 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
<a href="https://repogeo.com/en/r/ymcui/Chinese-XLNet"><img src="https://repogeo.com/badge/ymcui/Chinese-XLNet.svg" alt="RepoGEO" /></a>
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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
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