RRepoGEO

REPOGEO REPORT · LITE

Separius/awesome-fast-attention

Default branch master · commit 0d094bfd · scanned 5/29/2026, 9:47:34 PM

GitHub: 1,022 stars · 107 forks

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 Separius/awesome-fast-attention, 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
    Add a clear value proposition to the README introduction

    Why:

    CURRENT
    A curated list of efficient attention modules (last update: Wed, 10 Mar 2021 23:52:22 +0000)
    COPY-PASTE FIX
    A curated list of efficient attention modules. This resource helps researchers and developers discover and compare efficient attention mechanisms to improve transformer model performance and find faster alternatives to standard self-attention. (last update: [CURRENT DATE])
  • mediumtopics#2
    Add specific competitor model names to topics

    Why:

    CURRENT
    attention, attention-is-all-you-need, awesome, linformer, longformer, multihead-attention, reformer, self-attention, transformer, transformer-network
    COPY-PASTE FIX
    attention, attention-is-all-you-need, awesome, linformer, longformer, multihead-attention, reformer, self-attention, transformer, transformer-network, flashattention, bigbird, performer
  • lowhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    https://github.com/Separius/awesome-fast-attention

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 Separius/awesome-fast-attention
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
FlashAttention / FlashAttention-2
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. FlashAttention / FlashAttention-2 · recommended 2×
  2. Longformer · recommended 2×
  3. BigBird · recommended 2×
  4. Reformer · recommended 2×
  5. Linformer · recommended 2×
  • CATEGORY QUERY
    How to improve transformer model performance with more efficient attention mechanisms?
    you: not recommended
    AI recommended (in order):
    1. FlashAttention / FlashAttention-2
    2. Longformer
    3. BigBird
    4. Reformer
    5. Performer (Performer-ReLU)
    6. Linformer
    7. Nyströmformer

    AI recommended 7 alternatives but never named Separius/awesome-fast-attention. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking alternatives to standard self-attention for faster deep learning models.
    you: not recommended
    AI recommended (in order):
    1. FlashAttention / FlashAttention-2
    2. Performer
    3. Linformer
    4. Reformer
    5. Longformer
    6. BigBird
    7. Nyströmformer

    AI recommended 7 alternatives but never named Separius/awesome-fast-attention. 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 Separius/awesome-fast-attention?
    pass
    AI did not name Separius/awesome-fast-attention — 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 Separius/awesome-fast-attention in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Separius/awesome-fast-attention 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 Separius/awesome-fast-attention solve, and who is the primary audience?
    pass
    AI did not name Separius/awesome-fast-attention — 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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Separius/awesome-fast-attention — 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