RRepoGEO

REPOGEO REPORT · LITE

sail-sg/understand-r1-zero

Default branch main · commit dfca49dd · scanned 5/20/2026, 12:58:03 AM

GitHub: 1,257 stars · 59 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
33 /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
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 sail-sg/understand-r1-zero, 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 the README H1 to clarify it's a codebase and mention the framework

    Why:

    CURRENT
    # Understanding R1-Zero-Like Training: A Critical Perspective
    COPY-PASTE FIX
    # sail-sg/understand-r1-zero: Official Codebase for "Understanding R1-Zero-Like Training: A Critical Perspective" (Implemented with Oat RL Framework)
  • mediumabout#2
    Update the repository description to specify it's a codebase

    Why:

    CURRENT
    Understanding R1-Zero-Like Training: A Critical Perspective
    COPY-PASTE FIX
    Official codebase for "Understanding R1-Zero-Like Training: A Critical Perspective," implementing R1-Zero training with the Oat LLM RL framework.
  • mediumtopics#3
    Add more specific topics to improve categorization

    Why:

    CURRENT
    llm, r1-zero, reasoning, rl
    COPY-PASTE FIX
    llm, r1-zero, reasoning, rl, llm-training, rl-framework, mechanistic-interpretability, oat-framework

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 sail-sg/understand-r1-zero
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
R1-Zero
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. R1-Zero · recommended 1×
  2. AlphaZero · recommended 1×
  3. RLHF · recommended 1×
  4. Monte Carlo Tree Search (MCTS) · recommended 1×
  5. Transformers · recommended 1×
  • CATEGORY QUERY
    What are the current challenges in applying R1-Zero training to large language models?
    you: not recommended
    AI recommended (in order):
    1. R1-Zero
    2. AlphaZero
    3. RLHF
    4. Monte Carlo Tree Search (MCTS)
    5. Transformers
    6. CNNs

    AI recommended 6 alternatives but never named sail-sg/understand-r1-zero. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking methods to improve reasoning capabilities in LLMs using reinforcement learning techniques.
    you: not recommended
    AI recommended (in order):
    1. PPO (Proximal Policy Optimization)
    2. LLaMA-2-chat
    3. GPT-4
    4. DPO (Direct Preference Optimization)
    5. Claude 3 Opus
    6. Constitutional AI
    7. RLlib (ray-project/ray)
    8. Stable Baselines3 (DLR-RM/stable-baselines3)
    9. LangChain (langchain-ai/langchain)
    10. LlamaIndex (run-llama/llama_index)

    AI recommended 10 alternatives but never named sail-sg/understand-r1-zero. 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 sail-sg/understand-r1-zero?
    pass
    AI named sail-sg/understand-r1-zero explicitly

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

  • If a team adopts sail-sg/understand-r1-zero in production, what risks or prerequisites should they evaluate first?
    pass
    AI named sail-sg/understand-r1-zero 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 sail-sg/understand-r1-zero solve, and who is the primary audience?
    pass
    AI did not name sail-sg/understand-r1-zero — 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?

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MARKDOWN (README)
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sail-sg/understand-r1-zero — 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