RRepoGEO

REPOGEO REPORT · LITE

anguyen8/XAI-papers

Default branch master · commit dcdf3491 · scanned 6/2/2026, 10:27:43 AM

GitHub: 618 stars · 81 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 anguyen8/XAI-papers, 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
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A curated, ongoing collection of research papers, GUI tools, and libraries focused on Explainable Artificial Intelligence (XAI), for researchers and practitioners.
  • hightopics#2
    Add comprehensive topics to improve categorization

    Why:

    COPY-PASTE FIX
    explainable-ai, xai, machine-learning, deep-learning, research-papers, survey, literature-review, model-interpretability, ai-ethics, computer-vision, natural-language-processing
  • mediumreadme#3
    Clarify README's opening sentence to emphasize content type

    Why:

    CURRENT
    This is an on-going attempt to consolidate interesting efforts in the area of understanding / interpreting / explaining / visualizing *a pre-trained ML model*.
    COPY-PASTE FIX
    This repository is an on-going attempt to consolidate interesting *research papers, GUI tools, and libraries* in the area of understanding / interpreting / explaining / visualizing *a pre-trained ML model*.

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 anguyen8/XAI-papers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SHAP
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. SHAP · recommended 2×
  2. LIME · recommended 2×
  3. Captum · recommended 2×
  4. ELI5 · recommended 1×
  5. InterpretML · recommended 1×
  • CATEGORY QUERY
    What open-source libraries are available for interpreting and explaining deep learning models?
    you: not recommended
    AI recommended (in order):
    1. SHAP
    2. LIME
    3. Captum
    4. ELI5
    5. InterpretML
    6. TensorFlow Explain
    7. Alibi Explain

    AI recommended 7 alternatives but never named anguyen8/XAI-papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I visualize and understand the internal workings of pre-trained neural networks?
    you: not recommended
    AI recommended (in order):
    1. Captum
    2. LIME
    3. SHAP
    4. TensorBoard
    5. Grad-CAM
    6. DeepDream
    7. Lucid

    AI recommended 7 alternatives but never named anguyen8/XAI-papers. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 anguyen8/XAI-papers?
    pass
    AI did not name anguyen8/XAI-papers — 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 anguyen8/XAI-papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named anguyen8/XAI-papers 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 anguyen8/XAI-papers solve, and who is the primary audience?
    pass
    AI named anguyen8/XAI-papers 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 anguyen8/XAI-papers. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/anguyen8/XAI-papers.svg)](https://repogeo.com/en/r/anguyen8/XAI-papers)
HTML
<a href="https://repogeo.com/en/r/anguyen8/XAI-papers"><img src="https://repogeo.com/badge/anguyen8/XAI-papers.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

anguyen8/XAI-papers — 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