REPOGEO REPORT · LITE

huytransformer/Awesome-Out-Of-Distribution-Detection

Default branch main · commit 62520224 · scanned 5/21/2026, 7:57:22 PM

GitHub: 1,003 stars · 79 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

15 /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

0 / 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 huytransformer/Awesome-Out-Of-Distribution-Detection, 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

highhomepage#1
Add the repository URL to the 'Homepage' field in the About section
Why:
COPY-PASTE FIX
```
https://github.com/huytransformer/Awesome-Out-Of-Distribution-Detection
```

highreadme#2

Update the README H1 to explicitly include 'Awesome Resources'

Why:

CURRENT

# OOD Machine Learning: Detection, Robustness, and Generalization

COPY-PASTE FIX

# Awesome Out-Of-Distribution (OOD) Resources: Detection, Robustness, and Generalization

mediumabout#3

Refine the repository description to emphasize its 'Awesome List' nature

Why:

CURRENT

Out-of-distribution detection, robustness, and generalization resources. The repository contains a curated list of papers, tutorials, books, videos, articles and open-source libraries etc

COPY-PASTE FIX

An awesome list of out-of-distribution detection, robustness, and generalization resources. This repository contains a curated collection of papers, tutorials, books, videos, articles, and open-source libraries.

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 huytransformer/Awesome-Out-Of-Distribution-Detection

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Awesome-OOD-Detection

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Awesome-OOD-Detection · recommended 1×
OpenOOD · recommended 1×
Papers with Code · recommended 1×
PyTorch-OOD · recommended 1×
TensorFlow Probability · recommended 1×

CATEGORY QUERY
How to find comprehensive resources for out-of-distribution detection in machine learning models?
you: not recommended
AI recommended (in order):
1. Awesome-OOD-Detection
2. OpenOOD
3. Papers with Code
4. PyTorch-OOD
5. TensorFlow Probability
AI recommended 5 alternatives but never named huytransformer/Awesome-Out-Of-Distribution-Detection. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are effective strategies and tools for handling distribution shifts and novelty detection?
you: not recommended
AI recommended (in order):
1. Alibi Detect
2. Evidently AI
3. Seldon Core / Seldon Deploy
4. Fiddler AI
5. PyOD
6. TensorFlow Extended (TFX) / Kubeflow Pipelines
7. Apache Flink / Apache Kafka Streams
AI recommended 7 alternatives but never named huytransformer/Awesome-Out-Of-Distribution-Detection. 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 huytransformer/Awesome-Out-Of-Distribution-Detection?
pass
AI did not name huytransformer/Awesome-Out-Of-Distribution-Detection — 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 huytransformer/Awesome-Out-Of-Distribution-Detection in production, what risks or prerequisites should they evaluate first?
pass
AI did not name huytransformer/Awesome-Out-Of-Distribution-Detection — 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?
In one sentence, what problem does the repo huytransformer/Awesome-Out-Of-Distribution-Detection solve, and who is the primary audience?
pass
AI did not name huytransformer/Awesome-Out-Of-Distribution-Detection — 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 huytransformer/Awesome-Out-Of-Distribution-Detection. 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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huytransformer/Awesome-Out-Of-Distribution-Detection — 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