kakaobrain/coyo-dataset

• highlicense#1

  Add a LICENSE file to the repository

  原因：

  复制粘贴的修复

  复制

  Create a LICENSE file in the repository root with the appropriate license text (e.g., Apache-2.0, MIT, or a custom data license if applicable). If a custom license, also clarify its terms directly in the README.

  待办完成忽略
• mediumreadme#2

  Strengthen the unique value proposition in the README introduction

  原因：

  当前

  COYO-700M is a large-scale dataset that contains 747M image-text pairs as well as many other meta-attributes to increase the usability to train various models. Our dataset follows a similar strategy to previous vision-and-language datasets, collecting many informative pairs of alt-text and its associated image in HTML documents. We expect COYO to be used to train popular large-scale foundation models complementary to other similar datasets.

  复制粘贴的修复

  复制

  COYO-700M is a large-scale, high-quality dataset containing 747M image-text pairs, designed to train various multimodal foundation models. Unlike other datasets that prioritize raw scale, COYO-700M emphasizes stringent image and text-level filtering, including meta-attributes, to deliver a cleaner, more usable dataset complementary to existing resources. This focus on quality makes it ideal for researchers seeking robust data for advanced vision-language model pre-training.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  What are good large-scale image-text datasets for training multimodal foundation models?

  你：未被推荐
  AI 推荐顺序：

  1. LAION-5B
  2. Stable Diffusion
  3. LAION-400M
  4. LAION-2B-en
  5. ALIGN
  6. JFT-300M
  7. JFT-3B
  8. Conceptual Captions (CC3M)
  9. Conceptual Captions (CC12M)
  10. WIT (WebImageText)
  11. COYO-700M
  12. YFCC100M (Yahoo Flickr Creative Commons 100M)

  AI 推荐了 12 个替代方案，却始终没点名 kakaobrain/coyo-dataset。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Where can I find extensive image-text data for vision-language model pre-training?

  你：未被推荐
  AI 推荐顺序：

  1. LAION-5B
  2. Conceptual Captions (CC3M/CC12M)
  3. WIT (WebImageText)
  4. COCO (Common Objects in Context)
  5. Visual Genome
  6. SBU Captions
  7. YFCC100M (Yahoo Flickr Creative Commons 100M)

  AI 推荐了 7 个替代方案，却始终没点名 kakaobrain/coyo-dataset。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of kakaobrain/coyo-dataset?

  pass
  ⚠AI 未点名 kakaobrain/coyo-dataset —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts kakaobrain/coyo-dataset in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 kakaobrain/coyo-dataset

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo kakaobrain/coyo-dataset solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 kakaobrain/coyo-dataset

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？