REPOGEO REPORT · LITE

cmhungsteve/Awesome-Transformer-Attention

Default branch main · commit 0653f4a1 · scanned 6/29/2026, 3:02:51 PM

GitHub: 5,046 stars · 497 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 cmhungsteve/Awesome-Transformer-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

highlicense#1

Add a LICENSE file to the repository

Why:

CURRENT

(no LICENSE file detected)

COPY-PASTE FIX

Create a `LICENSE` file in the repository root with the MIT License text (or another suitable open-source license for content, e.g., CC-BY-4.0).

highhomepage#2

Set the repository homepage URL

Why:

COPY-PASTE FIX

Set the repository homepage URL in the repository settings to `https://github.com/cmhungsteve/Awesome-Transformer-Attention`.

mediumreadme#3

Add a 'Why this list?' or 'Key Features' section to the README

Why:

COPY-PASTE FIX

Add a new section to the README, for example, after the introduction, titled '## Why this list?' or '## Key Features', with content like: 'This list stands out due to its comprehensive and specialized focus on **Vision Transformer & Attention** mechanisms, curating papers, codes, and related websites specifically for researchers and practitioners in this niche.'

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 cmhungsteve/Awesome-Transformer-Attention

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

arXiv.org

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

arXiv.org · recommended 1×
Papers With Code · recommended 1×
Google Scholar · recommended 1×
Connected Papers · recommended 1×
awesome-vision-transformer/awesome-vision-transformer · recommended 1×

CATEGORY QUERY
Where can I find a comprehensive list of recent Vision Transformer and attention research papers?
you: not recommended
AI recommended (in order):
1. arXiv.org
2. Papers With Code
3. Google Scholar
4. Connected Papers
5. awesome-vision-transformer (awesome-vision-transformer/awesome-vision-transformer)
6. Awesome-Transformers (amanchadha/awesome-transformers)
7. OpenReview.net
8. Twitter
AI recommended 8 alternatives but never named cmhungsteve/Awesome-Transformer-Attention. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the key resources for understanding and implementing transformer models in computer vision?
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers Library
AI recommended 1 alternative but never named cmhungsteve/Awesome-Transformer-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 cmhungsteve/Awesome-Transformer-Attention?
pass
AI did not name cmhungsteve/Awesome-Transformer-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 cmhungsteve/Awesome-Transformer-Attention in production, what risks or prerequisites should they evaluate first?
pass
AI named cmhungsteve/Awesome-Transformer-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 cmhungsteve/Awesome-Transformer-Attention solve, and who is the primary audience?
pass
AI did not name cmhungsteve/Awesome-Transformer-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?

Embed your GEO score

Drop this badge into the README of cmhungsteve/Awesome-Transformer-Attention. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

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HTML

<a href="https://repogeo.com/en/r/cmhungsteve/Awesome-Transformer-Attention"><img src="https://repogeo.com/badge/cmhungsteve/Awesome-Transformer-Attention.svg" alt="RepoGEO" /></a>

Pro

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cmhungsteve/Awesome-Transformer-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