REPOGEO REPORT · LITE

youngfish42/Awesome-FL

Default branch main · commit 672a2a87 · scanned 5/16/2026, 5:37:14 PM

GitHub: 1,985 stars · 223 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

40 /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

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 youngfish42/Awesome-FL, 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 an explicit introductory sentence to the README

Why:

COPY-PASTE FIX

This is an awesome list: a comprehensive and timely collection of academic resources on federated learning, including papers, frameworks, datasets, tutorials, and workshops.

mediumabout#2

Update the repository's 'About' description to clarify its nature

Why:

CURRENT

Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

COPY-PASTE FIX

An awesome list: comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops).

lowtopics#3

Add 'awesome-list' to the repository topics

Why:

CURRENT

artificial-intelligence, awesome, computer-vision, data-mining, database, deep-learning, efficiency, federated-learning, federated-learning-framework, graph, graph-neural-networks, information-retrieval, knowledge-graph, machine-learning, natural-language-processing, paper, privacy, security, system, tabular-data

COPY-PASTE FIX

artificial-intelligence, awesome, awesome-list, computer-vision, data-mining, database, deep-learning, efficiency, federated-learning, federated-learning-framework, graph, graph-neural-networks, information-retrieval, knowledge-graph, machine-learning, natural-language-processing, paper, privacy, security, system, tabular-data

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 youngfish42/Awesome-FL

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Google AI Blog

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Google AI Blog · recommended 1×
arXiv.org · recommended 1×
Papers With Code · recommended 1×
Awesome Federated Learning · recommended 1×
IEEE Xplore · recommended 1×

CATEGORY QUERY
Where can I find a comprehensive collection of academic papers and frameworks for federated learning?
you: not recommended
AI recommended (in order):
1. Google AI Blog
2. arXiv.org
3. Papers With Code
4. Awesome Federated Learning
5. IEEE Xplore
6. ACM Digital Library
7. Mendeley
8. Zotero
9. OpenMined
10. PySyft
AI recommended 10 alternatives but never named youngfish42/Awesome-FL. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a curated list of federated learning frameworks and datasets for graph or tabular data.
you: not recommended
AI recommended (in order):
1. FedML
2. Flower
3. PySyft (OpenMined)
4. LEAF (Learning in Federated Settings)
5. TensorFlow Federated (TFF)
AI recommended 5 alternatives but never named youngfish42/Awesome-FL. 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 youngfish42/Awesome-FL?
pass
AI named youngfish42/Awesome-FL explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts youngfish42/Awesome-FL in production, what risks or prerequisites should they evaluate first?
pass
AI named youngfish42/Awesome-FL 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 youngfish42/Awesome-FL solve, and who is the primary audience?
pass
AI named youngfish42/Awesome-FL explicitly
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 youngfish42/Awesome-FL. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/youngfish42/Awesome-FL.svg)](https://repogeo.com/en/r/youngfish42/Awesome-FL)

HTML

<a href="https://repogeo.com/en/r/youngfish42/Awesome-FL"><img src="https://repogeo.com/badge/youngfish42/Awesome-FL.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

youngfish42/Awesome-FL — 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