RRepoGEO

REPOGEO REPORT · LITE

atfortes/Awesome-LLM-Reasoning

Default branch main · commit e01b133c · scanned 7/1/2026, 5:38:04 AM

GitHub: 3,641 stars · 211 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
22 /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
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 atfortes/Awesome-LLM-Reasoning, 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
  • highabout#1
    Update the repository's GitHub Description

    Why:

    CURRENT
    From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓
    COPY-PASTE FIX
    This repository helps researchers and practitioners discover and navigate key resources related to Large Language Model (LLM) reasoning by curating a comprehensive list of papers, datasets, and tools.
  • mediumhomepage#2
    Add a homepage link to a related project

    Why:

    COPY-PASTE FIX
    https://github.com/atfortes/LLMSymbolicReasoningBench
  • lowreadme#3
    Refine README opening to explicitly emphasize 'Awesome List' nature

    Why:

    CURRENT
    <p align="center">
    <b> Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.</b>
</p>
    COPY-PASTE FIX
    <p align="center">
    <b> An Awesome List: A curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.</b>
</p>

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 atfortes/Awesome-LLM-Reasoning
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GSM8K
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GSM8K · recommended 1×
  2. ARC · recommended 1×
  3. BigBench Hard · recommended 1×
  4. VL-T5 · recommended 1×
  5. Flamingo · recommended 1×
  • CATEGORY QUERY
    What are effective methods to enhance reasoning abilities in large language models?
    you: not recommended
    AI recommended (in order):
    1. GSM8K
    2. ARC
    3. BigBench Hard

    AI recommended 3 alternatives but never named atfortes/Awesome-LLM-Reasoning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find resources on improving multimodal reasoning capabilities in LLMs?
    you: not recommended
    AI recommended (in order):
    1. VL-T5
    2. Flamingo
    3. PaLM-E
    4. Transformers (huggingface/transformers)
    5. CLIP
    6. BLIP
    7. BLIP-2
    8. MMDetection (open-mmlab/mmdetection)
    9. MMDetection3D (open-mmlab/mmdetection3d)
    10. Llava (haotian-liu/LLaVA)
    11. InstructBLIP

    AI recommended 11 alternatives but never named atfortes/Awesome-LLM-Reasoning. 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 atfortes/Awesome-LLM-Reasoning?
    pass
    AI did not name atfortes/Awesome-LLM-Reasoning — 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 atfortes/Awesome-LLM-Reasoning in production, what risks or prerequisites should they evaluate first?
    pass
    AI named atfortes/Awesome-LLM-Reasoning 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 atfortes/Awesome-LLM-Reasoning solve, and who is the primary audience?
    pass
    AI did not name atfortes/Awesome-LLM-Reasoning — 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

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atfortes/Awesome-LLM-Reasoning — 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