RRepoGEO

REPOGEO REPORT · LITE

YingqingHe/Awesome-LLMs-meet-Multimodal-Generation

Default branch main · commit c508e82e · scanned 6/9/2026, 11:03:59 PM

GitHub: 545 stars · 31 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
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 YingqingHe/Awesome-LLMs-meet-Multimodal-Generation, 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 to clarify it's a list of papers/survey

    Why:

    CURRENT
    This repository contains a curated list of **LLMs meet multimodal generation**.
    COPY-PASTE FIX
    This repository serves as a comprehensive **curated list of academic papers** on LLMs meeting multimodal generation, including visual (image, video, 3D) and audio (sound, speech, music) modalities. It is a **survey of research**, not a software library or tool.
  • highlicense#2
    Add a LICENSE file

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with a standard open-source license (e.g., MIT, Apache-2.0, GPL-3.0) that best suits the project's intent for sharing and contributions.
  • mediumhomepage#3
    Add the survey paper URL as the repository homepage

    Why:

    COPY-PASTE FIX
    Add `https://arxiv.org/abs/2405.19334` as the repository's homepage URL in the GitHub repository settings.

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 YingqingHe/Awesome-LLMs-meet-Multimodal-Generation
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Stable Diffusion
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Stable Diffusion · recommended 2×
  2. ChatGPT · recommended 1×
  3. GPT-4o · recommended 1×
  4. Claude 3 Opus · recommended 1×
  5. Sonnet · recommended 1×
  • CATEGORY QUERY
    How can I generate diverse multimodal content like images, videos, and 3D with large language models?
    you: not recommended
    AI recommended (in order):
    1. ChatGPT
    2. GPT-4o
    3. Claude 3 Opus
    4. Sonnet
    5. LangChain
    6. LlamaIndex
    7. Google Gemini
    8. Stable Diffusion
    9. ControlNet
    10. IP-Adapter
    11. Stable Video Diffusion
    12. Midjourney
    13. RunwayML (Gen-2)
    14. Luma AI
    15. Genie
    16. Dream Machine
    17. Meshy
    18. Blockade Labs (Skybox AI)

    AI recommended 18 alternatives but never named YingqingHe/Awesome-LLMs-meet-Multimodal-Generation. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best resources for understanding LLM-based generation across visual and audio modalities?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. ViT (Vision Transformer)
    3. CLIP (Contrastive Language-Image Pre-training)
    4. DALL-E 2
    5. Stable Diffusion
    6. Whisper
    7. Audio Spectrogram Transformer (AST)
    8. Papers With Code
    9. OpenAI Research Papers & Blog
    10. DALL-E
    11. Google AI Blog & Research Papers
    12. PaLM-E (Pathways Language Model Embodied)
    13. Imagen
    14. PyTorch
    15. TensorFlow
    16. "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
    17. Yannic Kilcher
    18. AI Coffee Break with Letitia

    AI recommended 18 alternatives but never named YingqingHe/Awesome-LLMs-meet-Multimodal-Generation. 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 YingqingHe/Awesome-LLMs-meet-Multimodal-Generation?
    pass
    AI did not name YingqingHe/Awesome-LLMs-meet-Multimodal-Generation — 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 YingqingHe/Awesome-LLMs-meet-Multimodal-Generation in production, what risks or prerequisites should they evaluate first?
    pass
    AI named YingqingHe/Awesome-LLMs-meet-Multimodal-Generation 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 YingqingHe/Awesome-LLMs-meet-Multimodal-Generation solve, and who is the primary audience?
    pass
    AI did not name YingqingHe/Awesome-LLMs-meet-Multimodal-Generation — 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?

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YingqingHe/Awesome-LLMs-meet-Multimodal-Generation — 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