REPOGEO REPORT · LITE

showlab/Awesome-MLLM-Hallucination

Default branch main · commit dd23860a · scanned 5/15/2026, 12:33:17 AM

GitHub: 1,017 stars · 46 forks

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

highreadme#1

Clarify README's opening to emphasize 'Awesome List' nature

Why:

CURRENT

# Awesome MLLM Hallucination [](https://github.com/sindresorhus/awesome) 

## Hallucination of Multimodal Large Language Models: A Survey
### :star: News! The Latest & Most Comprehensive Survey on MLLM Hallucination Just Got Better!

COPY-PASTE FIX

# Awesome MLLM Hallucination: A Curated List of Resources for Multimodal Large Language Models

This repository is a comprehensive, curated list of papers, codes, datasets, and other resources dedicated to understanding and mitigating hallucination in Multimodal Large Language Models (MLLM), also known as Large Vision-Language Models (LVLM).

hightopics#2

Add relevant topics to the repository

Why:

COPY-PASTE FIX

awesome-list, multimodal-llm, mllm, lvlm, hallucination, ai-hallucination, large-language-models, llm, computer-vision, natural-language-processing, nlp, survey, research-papers

highlicense#3
Add a LICENSE file to the repository
Why:
COPY-PASTE FIX
```
Create a LICENSE file in the repository root with the content of 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

Of all named tools, what % are you?

Top rival

Wikidata

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Wikidata · recommended 2×
Scale AI · recommended 1×
Appen · recommended 1×
Surge AI · recommended 1×
FactScore · recommended 1×

CATEGORY QUERY
How to address and understand hallucination issues in multimodal large language models?
you: not recommended
AI recommended (in order):
1. Scale AI
2. Appen
3. Surge AI
4. FactScore
5. VisPro
6. POPE
7. MM-Vet
8. LIME
9. SHAP
10. Grad-CAM
11. Giskard
12. Arize AI
13. LangChain
14. LlamaIndex
15. Neo4j
16. Wikidata
AI recommended 16 alternatives but never named showlab/Awesome-MLLM-Hallucination. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking effective strategies and resources to mitigate visual-language model factual errors.
you: not recommended
AI recommended (in order):
1. LAION-5B
2. COCO
3. Visual Genome
4. Conceptual Captions
5. Wikidata
6. DBpedia
7. Google Knowledge Graph API
8. OpenAI's InstructGPT/ChatGPT approach
9. CLEVR
10. VCR
11. BLEU
12. ROUGE
13. CIDEr
14. SPICE
15. Hugging Face Transformers library (huggingface/transformers)
16. ViT-GPT2
17. BLIP
18. CLIP
AI recommended 18 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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MARKDOWN (README)

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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