tsinghua-fib-lab/World-Model

• highreadme#1

  Reposition README H1 and first sentence to emphasize survey companion role

  原因：

  当前

  # Awesome-World-Model [](https://github.com/sindresorhus/awesome)
  A curated list of awesome resources on World Models, based on the comprehensive survey "Understanding World or Predicting Future? A Comprehensive Survey of World Models".

  复制粘贴的修复

  复制

  # Understanding World or Predicting Future? A Comprehensive Survey of World Models (ACM CSUR 2025) - Official Companion Resources
  This repository serves as the official companion to our comprehensive survey paper.

  待办完成忽略
• mediumtopics#2

  Add topics that describe the repository's format (survey/resource list)

  原因：

  当前

  artificial-general-intelligence, embodied-intelligence, game-intelligence, societal-intelligence, urban-intelligence, world-models

  复制粘贴的修复

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  artificial-general-intelligence, embodied-intelligence, game-intelligence, societal-intelligence, urban-intelligence, world-models, survey, literature-review, awesome-list, research-resources, academic-paper-companion

  待办完成忽略
• mediumreadme#3

  Add a dedicated 'About' section to clarify the repository's purpose and audience

  原因：

  复制粘贴的修复

  复制

  ## About This Repository
  This repository provides a curated and regularly updated list of awesome resources, including key papers, code implementations, and datasets related to World Models. It is primarily intended for AI researchers, students, and practitioners seeking a foundational understanding and up-to-date overview of the field.

  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

  Where can I find a comprehensive overview of world models for AI research?

  你：未被推荐
  AI 推荐顺序：

  1. "World Models" by Ha and Schmidhuber (2018)
  2. "DreamerV3: Mastering Diverse Domains with World Models" by Hafner et al. (2023)
  3. "A Survey of World Models in Reinforcement Learning" by Weng et al. (2023)
  4. "Learning Latent Dynamics for Planning from Pixels" (PlaNet) by Hafner et al. (2019)
  5. "Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model" (MuZero) by Schrittwieser et al. (2020)
  6. "Recurrent World Models for Reinforcement Learning" by Ha and Schmidhuber (2018)
  7. "World Models: A Survey" by Wang et al. (2023)

  AI 推荐了 7 个替代方案，却始终没点名 tsinghua-fib-lab/World-Model。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What are the foundational concepts for building embodied intelligence in AI systems?

  你：未被推荐
  AI 推荐顺序：

  1. Intel RealSense

  AI 推荐了 1 个替代方案，却始终没点名 tsinghua-fib-lab/World-Model。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of tsinghua-fib-lab/World-Model?

  pass
  ⚠AI 未点名 tsinghua-fib-lab/World-Model —— 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 tsinghua-fib-lab/World-Model in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 tsinghua-fib-lab/World-Model

  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 tsinghua-fib-lab/World-Model solve, and who is the primary audience?

  pass
  ⚠AI 未点名 tsinghua-fib-lab/World-Model —— 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？