REPOGEO REPORT · LITE

wangyongjie-ntu/Awesome-explainable-AI

Default branch master · commit e0d200bb · scanned 5/12/2026, 2:07:46 PM

GitHub: 1,634 stars · 221 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 wangyongjie-ntu/Awesome-explainable-AI, 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

Clarify README's opening sentence to explicitly state it's an "Awesome list"

Why:

CURRENT

This repository contains the frontier research on explainable AI(XAI) which is a hot topic recently.

COPY-PASTE FIX

This Awesome list is a comprehensive collection of frontier research materials on Explainable AI (XAI), a rapidly evolving field.

highhomepage#2
Add the GitHub repository URL as the homepage
Why:
COPY-PASTE FIX
```
https://github.com/wangyongjie-ntu/Awesome-explainable-AI
```

mediumtopics#3

Add 'awesome-list' and 'awesome-xai' to the repository topics

Why:

CURRENT

counterfactual-explanations, explainable-ai, explanation-system, interpretability, interpretable-ai, recourse, xai, xml

COPY-PASTE FIX

counterfactual-explanations, explainable-ai, explanation-system, interpretability, interpretable-ai, recourse, xai, xml, awesome-list, awesome-xai

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 wangyongjie-ntu/Awesome-explainable-AI

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Explainable AI: Interpreting, Explaining and Trusting AI

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Explainable AI: Interpreting, Explaining and Trusting AI · recommended 1×
Interpretable Machine Learning: A Guide for Making Black Box Models Explainable · recommended 1×
DARPA XAI Program · recommended 1×
The Ethical Algorithm: The Science of Socially Aware Algorithm Design · recommended 1×
Trustworthy AI: A Computational Perspective · recommended 1×

CATEGORY QUERY
I need a comprehensive collection of research materials to learn about explainable AI.
you: not recommended
AI recommended (in order):
1. Explainable AI: Interpreting, Explaining and Trusting AI
2. Interpretable Machine Learning: A Guide for Making Black Box Models Explainable
3. DARPA XAI Program
4. The Ethical Algorithm: The Science of Socially Aware Algorithm Design
5. Trustworthy AI: A Computational Perspective
6. Explainable AI for Healthcare and Medicine
7. Practical Explainable AI: A Guide to Interpreting, Explaining, and Improving Machine Learning Models
AI recommended 7 alternatives but never named wangyongjie-ntu/Awesome-explainable-AI. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How can I find academic resources on model interpretability and counterfactual explanations?
you: not recommended
AI recommended (in order):
1. Google Scholar
2. arXiv
3. ACM Digital Library
4. IEEE Xplore
5. Semantic Scholar
6. Distill.pub
7. Interpretable Machine Learning
AI recommended 7 alternatives but never named wangyongjie-ntu/Awesome-explainable-AI. 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 wangyongjie-ntu/Awesome-explainable-AI?
pass
AI did not name wangyongjie-ntu/Awesome-explainable-AI — 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 wangyongjie-ntu/Awesome-explainable-AI in production, what risks or prerequisites should they evaluate first?
pass
AI named wangyongjie-ntu/Awesome-explainable-AI 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 wangyongjie-ntu/Awesome-explainable-AI solve, and who is the primary audience?
pass
AI did not name wangyongjie-ntu/Awesome-explainable-AI — 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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MARKDOWN (README)

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