REPOGEO REPORT · LITE

marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning

Default branch main · commit 240447ce · scanned 6/10/2026, 7:57:44 PM

GitHub: 598 stars · 40 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 marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning, 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

Explicitly state the repo is an 'Awesome List' in the README introduction

Why:

CURRENT

## Introduction
Recently, hyperbolic spaces have emerged...

COPY-PASTE FIX

Add the following line as the very first content after any badges/title in your README: 'This repository is an **Awesome List** of papers and resources on hyperbolic representation and deep learning.'

highlicense#2

Add a LICENSE file to the repository

Why:

COPY-PASTE FIX

Create a `LICENSE` file in the repository root. A common choice is the MIT License, which you can add by copying its text into the new file.

mediumhomepage#3

Add a homepage URL to the repository's About section

Why:

COPY-PASTE FIX

In the repository's 'About' section, add `https://github.com/marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning` as the homepage URL.

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 marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

GraphSAGE

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

GraphSAGE · recommended 1×
GAT · recommended 1×
R-GCN · recommended 1×
Tree-LSTMs · recommended 1×
Recursive Neural Networks · recommended 1×

CATEGORY QUERY
How to effectively represent hierarchical data structures using advanced embedding techniques?
you: not recommended
AI recommended (in order):
1. GraphSAGE
2. GAT
3. R-GCN
4. Tree-LSTMs
5. Recursive Neural Networks
6. Poincare Embeddings
7. Node2Vec
8. DeepWalk
9. BERT
10. GPT
11. TransE
12. RotatE
13. ComplEx
AI recommended 13 alternatives but never named marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are the benefits of using hyperbolic models for graph or knowledge graph embeddings?
you: not recommended
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 marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning?
pass
AI did not name marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning — 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 marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning in production, what risks or prerequisites should they evaluate first?
pass
AI named marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning 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 marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning solve, and who is the primary audience?
pass
AI did not name marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning — 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 marlin-codes/Awesome-Hyperbolic-Representation-and-Deep-Learning. 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

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite