RRepoGEO

REPOGEO REPORT · LITE

LeapLabTHU/Absolute-Zero-Reasoner

Default branch master · commit 484afa48 · scanned 5/17/2026, 10:02:51 AM

GitHub: 1,852 stars · 300 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
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 LeapLabTHU/Absolute-Zero-Reasoner, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    reinforcement-learning, self-play, reasoning, large-language-models, neuro-symbolic-ai, zero-data-learning, logical-inference
  • highabout#2
    Improve the repository description for clarity

    Why:

    CURRENT
    Official Repository of Absolute Zero Reasoner
    COPY-PASTE FIX
    A neuro-symbolic reasoner leveraging LLMs for hypothesis generation and a symbolic engine for logical inference, trained with reinforced self-play on zero data.
  • mediumreadme#3
    Add a concise problem/solution statement to the README opening

    Why:

    COPY-PASTE FIX
    Absolute Zero addresses the critical challenge of training powerful AI reasoning models without relying on extensive pre-labeled datasets. It achieves this by leveraging reinforced self-play, combining large language models for hypothesis generation with a symbolic reasoning engine for robust logical inference.

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 LeapLabTHU/Absolute-Zero-Reasoner
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-4
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4 · recommended 1×
  2. Claude 3 Opus · recommended 1×
  3. Gemini 1.5 Pro · recommended 1×
  4. Llama 3 · recommended 1×
  5. huggingface/transformers · recommended 1×
  • CATEGORY QUERY
    How can I train a powerful reasoning model without relying on extensive pre-labeled datasets?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus
    3. Gemini 1.5 Pro
    4. Llama 3
    5. Hugging Face Transformers (huggingface/transformers)
    6. TRL library (huggingface/trl)
    7. DeepSpeed-Chat (microsoft/DeepSpeed-Chat)
    8. PyTorch Geometric (pyg-team/pytorch_geometric)
    9. DGL (dmlc/dgl)
    10. DreamCoder (probcomp/DreamCoder)
    11. AlphaCode

    AI recommended 11 alternatives but never named LeapLabTHU/Absolute-Zero-Reasoner. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks enable self-play reinforcement learning for enhancing AI reasoning abilities?
    you: not recommended
    AI recommended (in order):
    1. OpenSpiel
    2. RLlib
    3. AlphaZero
    4. Leela Chess Zero
    5. Leela Zero
    6. DeepMind Lab
    7. PettingZoo
    8. Stable Baselines3

    AI recommended 8 alternatives but never named LeapLabTHU/Absolute-Zero-Reasoner. 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 LeapLabTHU/Absolute-Zero-Reasoner?
    pass
    AI named LeapLabTHU/Absolute-Zero-Reasoner explicitly

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

  • If a team adopts LeapLabTHU/Absolute-Zero-Reasoner in production, what risks or prerequisites should they evaluate first?
    pass
    AI named LeapLabTHU/Absolute-Zero-Reasoner 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 LeapLabTHU/Absolute-Zero-Reasoner solve, and who is the primary audience?
    pass
    AI named LeapLabTHU/Absolute-Zero-Reasoner 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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LeapLabTHU/Absolute-Zero-Reasoner — 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