RRepoGEO

REPOGEO REPORT · LITE

showlab/Awesome-MLLM-Hallucination

Default branch main · commit dd23860a · scanned 6/25/2026, 2:53:16 PM

GitHub: 1,027 stars · 47 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
17 /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
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 showlab/Awesome-MLLM-Hallucination, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    multimodal-llm, mllm, llm-hallucination, hallucination, large-language-models, survey, awesome-list, research-papers, computer-vision, natural-language-processing, ai-safety
  • highreadme#2
    Clarify README's opening statement about repo type

    Why:

    CURRENT
    # Awesome MLLM Hallucination [](https://github.com/sindresorhus/awesome)
    COPY-PASTE FIX
    # Awesome MLLM Hallucination: A Curated List of Resources and Comprehensive Survey on Multimodal LLM Hallucination
  • mediumlicense#3
    Create a LICENSE file

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root directory with the `MIT License`.

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 showlab/Awesome-MLLM-Hallucination
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenImages V6/V7
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenImages V6/V7 · recommended 1×
  2. LAION-5B · recommended 1×
  3. Amazon Mechanical Turk · recommended 1×
  4. Scale AI · recommended 1×
  5. ViLT · recommended 1×
  • CATEGORY QUERY
    What are the common causes and effective mitigation strategies for multimodal AI model hallucinations?
    you: not recommended
    AI recommended (in order):
    1. OpenImages V6/V7
    2. LAION-5B
    3. Amazon Mechanical Turk
    4. Scale AI
    5. ViLT
    6. Flamingo
    7. BLIP
    8. Wikipedia
    9. Google Knowledge Graph
    10. LangChain
    11. LlamaIndex
    12. LIME
    13. SHAP
    14. Grad-CAM

    AI recommended 14 alternatives but never named showlab/Awesome-MLLM-Hallucination. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a comprehensive overview of recent advancements in reducing MLLM factual errors?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. Papers With Code
    4. NeurIPS
    5. ICML
    6. ICLR
    7. ACL
    8. EMNLP
    9. CVPR
    10. ICCV
    11. Google AI Blog
    12. Meta AI Blog
    13. OpenAI Blog
    14. Microsoft Research Blog
    15. Hugging Face Blog/Research

    AI recommended 15 alternatives but never named showlab/Awesome-MLLM-Hallucination. 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 showlab/Awesome-MLLM-Hallucination?
    pass
    AI did not name showlab/Awesome-MLLM-Hallucination — 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 showlab/Awesome-MLLM-Hallucination in production, what risks or prerequisites should they evaluate first?
    pass
    AI named showlab/Awesome-MLLM-Hallucination 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 showlab/Awesome-MLLM-Hallucination solve, and who is the primary audience?
    pass
    AI did not name showlab/Awesome-MLLM-Hallucination — 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

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showlab/Awesome-MLLM-Hallucination — 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