RRepoGEO

REPOGEO REPORT · LITE

SKTBrain/KoBERT

Default branch master · commit fcd729f2 · scanned 5/22/2026, 2:23:17 AM

GitHub: 1,408 stars · 379 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
81 /100
Healthy
Category recall
2 / 2
Avg rank #1.0 when recommended
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 SKTBrain/KoBERT, 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
  • highhomepage#1
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    [Your project's official homepage URL, e.g., a project page, documentation site, or organization page]
  • mediumreadme#2
    Expand the 'Why' section in the README to highlight KoBERT's unique benefits

    Why:

    CURRENT
    ### Why'?''

* 구글 BERT base multilingual cased의 한국어 성능 한계
    COPY-PASTE FIX
    ### Why KoBERT?

*   **Addressing Multilingual BERT's Korean Limitations:** Google's BERT base multilingual cased model often exhibits performance limitations when applied to the nuances of the Korean language. KoBERT is specifically pre-trained on a massive Korean corpus to overcome these challenges, providing superior accuracy and understanding for Korean NLP tasks.
*   **Optimized for Korean Text:** By focusing exclusively on Korean, KoBERT captures linguistic specificities, idiomatic expressions, and grammatical structures more effectively than general-purpose models, making it the ideal choice for robust Korean natural language processing.
  • lowtopics#3
    Add more specific topics to enhance discoverability

    Why:

    CURRENT
    bert, korean-nlp, language-model, nlp, pytorch, transformers
    COPY-PASTE FIX
    bert, korean-nlp, language-model, nlp, pytorch, transformers, deep-learning, ai-model

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
2 / 2
100% of queries surface SKTBrain/KoBERT
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
18%
Of all named tools, what % are you?
Top rival
KR-BERT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. KR-BERT · recommended 2×
  2. KoELECTRA · recommended 2×
  3. KcBERT · recommended 2×
  4. KoBART · recommended 2×
  5. KoGPT · recommended 1×
  • CATEGORY QUERY
    Need a pre-trained language model for robust Korean natural language processing tasks.
    you: #1
    AI recommended (in order):
    1. KoBERT ← you
    2. KR-BERT
    3. KoELECTRA
    4. KcBERT
    5. KoGPT
    6. KoBART
    Show full AI answer
  • CATEGORY QUERY
    Looking for a specialized BERT model improving performance on Korean text over multilingual versions.
    you: #1
    AI recommended (in order):
    1. KoBERT ← you
    2. KR-BERT
    3. KcBERT
    4. KoELECTRA
    5. KoBART
    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 SKTBrain/KoBERT?
    pass
    AI did not name SKTBrain/KoBERT — 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 SKTBrain/KoBERT in production, what risks or prerequisites should they evaluate first?
    pass
    AI named SKTBrain/KoBERT 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 SKTBrain/KoBERT solve, and who is the primary audience?
    pass
    AI named SKTBrain/KoBERT 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 SKTBrain/KoBERT. 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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SKTBrain/KoBERT — 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