LirongWu/awesome-graph-self-supervised-learning

• highabout#1

  Clarify repository description to reflect 'awesome list' nature

  原因：

  当前

  Code for TKDE paper "Self-supervised learning on graphs: Contrastive, generative, or predictive"

  复制粘贴的修复

  复制

  A curated list of resources for self-supervised learning on graphs, covering contrastive, generative, and predictive methods.

  待办完成忽略
• highlicense#2

  Add a LICENSE file to the repository

  原因：

  复制粘贴的修复

  复制

  Create a LICENSE file (e.g., MIT or Apache-2.0) in the repository root to clearly state the terms of use for the curated list and any associated content.

  待办完成忽略
• mediumhomepage#3

  Add a homepage URL to the repository metadata

  原因：

  复制粘贴的修复

  复制

  Add the URL of the associated TKDE paper or a project page (if one exists) to the repository's homepage 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

  How to learn effective graph representations using self-supervised methods for downstream tasks?

  你：未被推荐
  AI 推荐顺序：

  1. PyTorch Geometric (PyG)
  2. Deep Graph Library (DGL)
  3. Spektral
  4. GraphVPR (Graph Contrastive Learning Toolkit)
  5. Open Graph Benchmark (OGB)
  6. GraphGym

  AI 推荐了 6 个替代方案，却始终没点名 LirongWu/awesome-graph-self-supervised-learning。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What are the best techniques for pre-training graph neural networks using unsupervised learning?

  你：未被推荐
  AI 推荐顺序：

  1. Deep Graph Infomax (DGI)
  2. GraphCL
  3. GRACE
  4. BGRL
  5. CCA-SSG
  6. GraphMAE
  7. GraphBERT
  8. GraphRNN
  9. NetGAN
  10. GraphVAE
  11. Node2Vec
  12. DeepWalk
  13. LINE

  AI 推荐了 13 个替代方案，却始终没点名 LirongWu/awesome-graph-self-supervised-learning。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 LirongWu/awesome-graph-self-supervised-learning?

  pass
  ⚠AI 未点名 LirongWu/awesome-graph-self-supervised-learning —— 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 LirongWu/awesome-graph-self-supervised-learning in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 LirongWu/awesome-graph-self-supervised-learning

  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 LirongWu/awesome-graph-self-supervised-learning solve, and who is the primary audience?

  pass
  ⚠AI 未点名 LirongWu/awesome-graph-self-supervised-learning —— 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？