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ACG-SimpleQA

Tasks:
Text Generation
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Text
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json
Languages:
Chinese
Size:
1K - 10K
Tags:
ACG
animation
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metadata
license: mit
task_categories:
  - text-generation
language:
  - zh
tags:
  - ACG
  - animation
size_categories:
  - 1K<n<10K

ACG-SimpleQA

🌐 Website β€’ πŸ€— Hugging Face
δΈ­ζ–‡ | English

ACG-SimpleQA is an objective knowledge question-answering dataset focused on the Chinese ACG (Animation, Comic, Game) domain, containing 4242 auto-generated carefully designed QA samples. This benchmark aims to evaluate large language models' factual capabilities in the ACG culture domain, featuring Chinese language, diversity, high quality, static answers, and easy evaluation.

πŸ“’ Latest Updates

  • [2025.04.24] We officially release the ACG-SimpleQA dataset! Welcome to download it from πŸ€—Hugging Face

πŸ’« Introduction

ACG-SimpleQA is a comprehensive benchmark designed to test large language models' factual knowledge in the ACG culture domain. The dataset features:

  • πŸ€„ Chinese: ACG-SimpleQA focuses on Chinese ACG knowledge, providing a thorough evaluation of LLMs' factual abilities in this area.
  • πŸ€ Diversity: Covers multiple subdomains such as anime, games, manga, and music, ensuring comprehensive assessment.
  • ⚑ High Quality: Strict quality control ensures the accuracy of questions and answers.
  • πŸ’‘ Static: All reference answers are time-invariant, and the knowledge cutoff is before 2024, ensuring long-term validity.
  • πŸ—‚οΈ Easy Evaluation: The evaluation method is consistent with SimpleQA and ChineseSimpleQA.

πŸ“Š Leaderboard

Model ACG-SimpleQA
gemini-2.5-pro-preview-03-25 0.5434
gpt-4.5-preview 0.4884
gemini-2.5-flash-preview-04-17 0.3993
deepseek-v3-241226 0.3963
deepseek-v3-250324 0.3944
gpt-4.1 0.3880
grok-3-beta 0.3810
chatgpt-4o-latest 0.3758
gemini-2.0-flash-001 0.3597
minimax-01 0.3175
gemini-2.0-flash-lite-001 0.2897
claude-3.7-sonnet 0.2864
glm-4-plus 0.2659
claude-3.5-sonnet 0.2515
qwen-max 0.2466
doubao-1.5-pro-32k-250115 0.2435
grok-3-mini-beta 0.2357
o4-mini 0.2263
llama-4-maverick 0.1655
gpt-4.1-mini 0.1610
glm-4-air-250414 0.1412
claude-3.5-haiku 0.1334
gemma-3-27b-it 0.1247
llama-3.3-70b-instruct 0.1106
qwq-32b 0.0974
qwen2.5-32b-instruct 0.0969
gpt-4.1-nano 0.0957
glm-4-flash-250414 0.0700
gemma-3-4b-it 0.0370

πŸ“œ Citation

If you use this repository in your research, please consider citing:

@misc{pka2025acgsimpleqa,
    title={ACG-SimpleQA},
    author={Papersnake},
    howpublished = {\url{https://github.com/prnake/ACG-SimpleQA}},
    year={2025}
}