RRepoGEO

REPOGEO REPORT · LITE

RUC-GSAI/YuLan-Chat

Default branch main · commit 6d891efa · scanned 6/13/2026, 12:03:04 PM

GitHub: 636 stars · 58 forks

AI VISIBILITY SCORE
40 /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
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 RUC-GSAI/YuLan-Chat, 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 opening to clarify core identity and correct AI's misunderstanding

    Why:

    CURRENT
    YuLan-Chat models are chat-based large language models, which are developed by the researchers in GSAI, Renmin University of China (YuLan, which represents Yulan Magnolia, is the campus flower of Renmin University of China). The newest version is developed by pre-training from scratch, and supervised fine-tuning via curriculum learning with high-quality English and Chinese instructions and human preference data.
    COPY-PASTE FIX
    YuLan-Chat is an open-source, chat-based large language model (LLM), developed from scratch by researchers at Renmin University of China. Unlike multimodal models, YuLan-Chat focuses purely on language, excelling in both English and Chinese through supervised fine-tuning via curriculum learning with high-quality instructions and human preference data, ensuring strong human alignment and safety features.
  • hightopics#2
    Add more specific topics to improve categorization and recall

    Why:

    CURRENT
    large-language-models
    COPY-PASTE FIX
    large-language-models, chat-llm, chinese-llm, multilingual-llm, human-alignment, pre-trained-llm
  • mediumreadme#3
    Add a 'Comparison' section to highlight differentiators

    Why:

    COPY-PASTE FIX
    ## Comparison & Differentiators

YuLan-Chat stands out among open-source large language models by offering a unique combination of 'from scratch' pre-training, advanced curriculum learning for human alignment, and robust performance optimized for both English and Chinese chat applications, distinguishing it from models like Qwen, Baichuan, and LLaMA 3.

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 RUC-GSAI/YuLan-Chat
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Qwen
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Qwen · recommended 1×
  2. Baichuan · recommended 1×
  3. Yi · recommended 1×
  4. DeepSeek · recommended 1×
  5. LLaMA 3 · recommended 1×
  • CATEGORY QUERY
    What open-source large language models offer strong performance for both English and Chinese?
    you: not recommended
    AI recommended (in order):
    1. Qwen
    2. Baichuan
    3. Yi
    4. DeepSeek
    5. LLaMA 3
    6. Mistral

    AI recommended 6 alternatives but never named RUC-GSAI/YuLan-Chat. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a robust, pre-trained, chat-optimized LLM with strong human alignment and safety features.
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus
    3. Gemini 1.5 Pro
    4. Llama 3 (meta-llama/llama3)
    5. Mistral Large

    AI recommended 5 alternatives but never named RUC-GSAI/YuLan-Chat. 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 RUC-GSAI/YuLan-Chat?
    pass
    AI named RUC-GSAI/YuLan-Chat explicitly

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

  • If a team adopts RUC-GSAI/YuLan-Chat in production, what risks or prerequisites should they evaluate first?
    pass
    AI named RUC-GSAI/YuLan-Chat 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 RUC-GSAI/YuLan-Chat solve, and who is the primary audience?
    pass
    AI named RUC-GSAI/YuLan-Chat 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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RUC-GSAI/YuLan-Chat — 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