REPOGEO REPORT · LITE

baaivision/tokenize-anything

Default branch main · commit 9cefd56a · scanned 6/13/2026, 7:33:32 AM

GitHub: 602 stars · 27 forks

AI VISIBILITY SCORE

35 /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

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 baaivision/tokenize-anything, 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

Reposition README opening to emphasize universal, zero-shot foundation model capabilities

Why:

CURRENT

We present **T**okenize **A**nything via **P**rompting, a unified and promptable model capable of simultaneously segmenting, recognizing, and captioning arbitrary regions, with flexible visual prompts (point, box and sketch). The model is trained with exhaustive segmentation masks sourced from SA-1B, coupled with semantic priors from a pre-trained EVA-CLIP with 5 billion parameters.

COPY-PASTE FIX

We present **T**okenize **A**nything via **P**rompting (TAP), a **universal and zero-shot foundation model** for comprehensive visual region understanding. TAP is a unified and promptable model capable of simultaneously segmenting, recognizing, and captioning arbitrary regions, with flexible visual prompts (point, box and sketch). It aims to provide **modality-agnostic tokenization** for diverse data types.

mediumabout#2
Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIX
```
https://arxiv.org/abs/XXXX.XXXXX (or the official project page/demo link)
```

mediumtopics#3

Expand repository topics with specific task keywords

Why:

CURRENT

foundation-models, multimodal, promptable, representation-learning

COPY-PASTE FIX

foundation-models, multimodal, promptable, representation-learning, image-segmentation, object-recognition, image-captioning, zero-shot-learning, visual-prompts

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 baaivision/tokenize-anything

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

CLIP

Recommended in 3 of 2 queries

COMPETITOR LEADERBOARD

CLIP · recommended 3×
BLIP-2 · recommended 3×
SAM · recommended 3×
Segment Anything Model (SAM) · recommended 2×
Grounding DINO · recommended 2×

CATEGORY QUERY
How to perform multimodal image segmentation, recognition, and captioning using visual prompts?
you: not recommended
AI recommended (in order):
1. Segment Anything Model (SAM)
2. CLIP
3. BLIP-2
4. Grounding DINO
5. SAM
6. LLaVA
7. OWL-ViT
8. SAM
9. MiniGPT-4
10. YOLO-World
11. SAM
12. InstructBLIP
13. Mask2Former
14. PanopticFPN
15. K-Net
16. CLIP
17. BLIP-2
18. LLaVA
AI recommended 18 alternatives but never named baaivision/tokenize-anything. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a promptable foundation model for comprehensive visual region understanding.
you: not recommended
AI recommended (in order):
1. Grounding DINO
2. OWL-ViT
3. Segment Anything Model (SAM)
4. CLIP
5. BLIP-2
6. Florence-2
AI recommended 6 alternatives but never named baaivision/tokenize-anything. 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 baaivision/tokenize-anything?
pass
AI named baaivision/tokenize-anything explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts baaivision/tokenize-anything in production, what risks or prerequisites should they evaluate first?
pass
AI named baaivision/tokenize-anything 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 baaivision/tokenize-anything solve, and who is the primary audience?
pass
AI named baaivision/tokenize-anything 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 baaivision/tokenize-anything. 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/baaivision/tokenize-anything.svg)](https://repogeo.com/en/r/baaivision/tokenize-anything)

HTML

<a href="https://repogeo.com/en/r/baaivision/tokenize-anything"><img src="https://repogeo.com/badge/baaivision/tokenize-anything.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

baaivision/tokenize-anything — 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