RRepoGEO

REPOGEO REPORT · LITE

ChaofanTao/Autoregressive-Models-in-Vision-Survey

Default branch main · commit 486b68a3 · scanned 6/10/2026, 6:08:58 PM

GitHub: 795 stars · 23 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 ChaofanTao/Autoregressive-Models-in-Vision-Survey, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root, for example, using the MIT License text.
  • highabout#2
    Expand the repository's 'About' description

    Why:

    CURRENT
    [TMLR 2025🔥] A survey for the autoregressive models in vision.
    COPY-PASTE FIX
    [TMLR 2025🔥] A comprehensive, curated survey and resource for the latest advancements in autoregressive models in computer vision, designed for researchers and practitioners.
  • mediumreadme#3
    Refine the README's introductory paragraph for direct utility

    Why:

    CURRENT
    Autoregressive models have shown significant progress in generating high-quality content by modeling the dependencies sequentially. This repo is a curated list of papers about the latest advancements in autoregressive models in vision.
    COPY-PASTE FIX
    This repository serves as a comprehensive, curated survey and definitive resource for the latest advancements in autoregressive models in computer vision. It provides a structured overview of papers, designed for researchers and practitioners seeking to understand and explore this rapidly evolving field.

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 ChaofanTao/Autoregressive-Models-in-Vision-Survey
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv.org
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv.org · recommended 1×
  2. Papers With Code · recommended 1×
  3. Distill.pub · recommended 1×
  4. Google Scholar · recommended 1×
  5. CVPR · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive overview of recent advancements in autoregressive models for computer vision tasks?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Papers With Code
    3. Distill.pub
    4. Google Scholar
    5. CVPR
    6. ICCV
    7. ECCV
    8. NeurIPS
    9. The Batch
    10. OpenAI Blog

    AI recommended 10 alternatives but never named ChaofanTao/Autoregressive-Models-in-Vision-Survey. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the latest developments in using autoregressive deep learning for multimodal content generation?
    you: not recommended
    AI recommended (in order):
    1. Gemini
    2. GPT-4o
    3. Lumiere
    4. Sora
    5. Emu Video
    6. Emu Edit
    7. MusicLM
    8. AudioCraft
    9. MusicGen
    10. AudioGen
    11. EnCodec
    12. Jukebox
    13. RT-2
    14. Gato

    AI recommended 14 alternatives but never named ChaofanTao/Autoregressive-Models-in-Vision-Survey. 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 ChaofanTao/Autoregressive-Models-in-Vision-Survey?
    pass
    AI did not name ChaofanTao/Autoregressive-Models-in-Vision-Survey — 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 ChaofanTao/Autoregressive-Models-in-Vision-Survey in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name ChaofanTao/Autoregressive-Models-in-Vision-Survey — 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 ChaofanTao/Autoregressive-Models-in-Vision-Survey solve, and who is the primary audience?
    pass
    AI did not name ChaofanTao/Autoregressive-Models-in-Vision-Survey — 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 ChaofanTao/Autoregressive-Models-in-Vision-Survey. 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/ChaofanTao/Autoregressive-Models-in-Vision-Survey.svg)](https://repogeo.com/en/r/ChaofanTao/Autoregressive-Models-in-Vision-Survey)
HTML
<a href="https://repogeo.com/en/r/ChaofanTao/Autoregressive-Models-in-Vision-Survey"><img src="https://repogeo.com/badge/ChaofanTao/Autoregressive-Models-in-Vision-Survey.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

ChaofanTao/Autoregressive-Models-in-Vision-Survey — 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