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zhijing-jin/nlp-phd-global-equality

默认分支 main · commit bec39dc4 · 扫描时间 2026/6/23 14:38:54

星标 1,070 · Fork 89

本仓库扫描历史

下方为分数趋势(含全部就绪扫描;左旧右新,可横向滚动)。表格明细默认折叠,展开后每页 10 条,最新在上。

分数趋势(左 → 右:旧 → 新)

共 2 条就绪扫描。点击下方按钮展开表格(每页 10 条,可翻页)。

AI 可见性总分
23 /100
亟需修复
品类召回
0 / 2
在所有问题中均未被推荐
规则结果
通过 1 · 警告 0 · 失败 1
客观元数据检查
AI 认识你的名字
2 / 3
直接询问时,AI 是否点名你的仓库
如何阅读这份报告

行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 zhijing-jin/nlp-phd-global-equality 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。

行动计划 — 可复制粘贴的修复

3 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。

整体方向
  • hightopics#1
    Add relevant topics to the repository

    原因:

    当前
    (none)
    复制粘贴的修复
    nlp, phd, ai, career-guidance, mentorship, global-equality, academic-resources, research-career, higher-education
  • highreadme#2
    Clarify the repository's purpose in the README's opening paragraph

    原因:

    当前
    This repo originates with a wish to promote **Global Equality** for people who want to do a PhD in NLP, following the idea that mentorship programs are an effective way to fight against segregation, according to The Human Networks (Jackson, 2019). Specifically, we wish people from all over the world and with all types of backgrounds can share the same source of information, so that success will be a reward to those who are determined and hardworking, regardless of external contrainsts.
    复制粘贴的修复
    This repository is a curated collection of open resources and information designed to promote **Global Equality** for individuals pursuing a PhD in NLP and careers in AI. It aims to provide a shared source of knowledge, mentorship insights, and guidance for aspiring NLP PhD students from all backgrounds, ensuring success is a reward for determination regardless of external constraints.
  • highlicense#3
    Add a LICENSE file or clarify license in README

    原因:

    当前
    (no LICENSE file detected)
    复制粘贴的修复
    Create a LICENSE file in the repository root (e.g., MIT, Apache-2.0, or CC-BY-4.0 for content), or explicitly state the applicable license(s) for the content within the README.

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

品类可见性 — 真正的 GEO 测试

向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?

各模型使用同一组问题 — 切换标签对比回答与排名。

召回
0 / 2
0% 的问题里出现了 zhijing-jin/nlp-phd-global-equality
平均排名
越小越好。#1 表示首位推荐。
声量占比
0%
在所有被点名的工具中,你占了多少?
头号对手
Twitter
在 2 个问题中被推荐 2 次
竞品排行
  1. Twitter · 被推荐 2 次
  2. Speech and Language Processing by Jurafsky and Martin · 被推荐 1 次
  3. Deep Learning by Goodfellow, Bengio, and Courville · 被推荐 1 次
  4. Stanford CS224N: Natural Language Processing with Deep Learning · 被推荐 1 次
  5. huggingface/transformers · 被推荐 1 次
  • 品类问题
    What resources help prepare for a successful NLP PhD application and academic journey?
    你:未被推荐
    AI 推荐顺序:
    1. Speech and Language Processing by Jurafsky and Martin
    2. Deep Learning by Goodfellow, Bengio, and Courville
    3. Stanford CS224N: Natural Language Processing with Deep Learning
    4. Hugging Face Transformers Library (huggingface/transformers)
    5. PyTorch (pytorch/pytorch)
    6. TensorFlow (tensorflow/tensorflow)
    7. Kaggle NLP Competitions
    8. ACL Anthology
    9. arXiv.org
    10. Twitter

    AI 推荐了 10 个替代方案,却始终没点名 zhijing-jin/nlp-phd-global-equality。这就是要补上的差距。

    查看 AI 完整回答
  • 品类问题
    Seeking comprehensive guidance for pursuing a career in AI research and academia globally.
    你:未被推荐
    AI 推荐顺序:
    1. MIT (Massachusetts Institute of Technology)
    2. Stanford University
    3. Carnegie Mellon University (CMU)
    4. University of California, Berkeley (UC Berkeley)
    5. University of Cambridge
    6. ETH Zurich
    7. Tsinghua University
    8. Python
    9. C++
    10. Java
    11. PyTorch
    12. TensorFlow
    13. NumPy
    14. Pandas
    15. Scikit-learn
    16. "Linear Algebra and Its Applications" by Gilbert Strang
    17. "Probability and Statistics for Engineers and Scientists" by Walpole, Myers, Ye
    18. Khan Academy
    19. Coursera
    20. Imperial College London
    21. University of Toronto
    22. Vector Institute
    23. University College London
    24. EPFL (École Polytechnique Fédérale de Lausanne)
    25. University of Washington
    26. University of Oxford
    27. Mila - Quebec AI Institute
    28. Université de Montréal
    29. McGill University
    30. Google Brain
    31. DeepMind
    32. Meta AI (FAIR)
    33. Microsoft Research
    34. OpenAI
    35. NVIDIA Research
    36. IBM Research AI
    37. Amazon AI
    38. NeurIPS (Conference on Neural Information Processing Systems)
    39. ICML (International Conference on Machine Learning)
    40. CVPR (Conference on Computer Vision and Pattern Recognition)
    41. ICCV (International Conference on Computer Vision)
    42. ACL (Association for Computational Linguistics)
    43. EMNLP (Empirical Methods in Natural Language Processing)
    44. AAAI (Association for the Advancement of Artificial Intelligence Conference)
    45. IJCAI (International Joint Conference on Artificial Intelligence)
    46. Reddit
    47. Twitter
    48. Discord servers
    49. GitHub

    AI 推荐了 49 个替代方案,却始终没点名 zhijing-jin/nlp-phd-global-equality。这就是要补上的差距。

    查看 AI 完整回答

客观检查

针对 AI 引擎最看重的元数据信号的规则审计。

  • Metadata completeness
    fail

    建议:

  • README presence
    pass

自指检查

当被直接问到你时,AI 是否还知道你的仓库存在?

  • Compared to common alternatives in this category, what is the core differentiator of zhijing-jin/nlp-phd-global-equality?
    pass
    AI 明确点名了 zhijing-jin/nlp-phd-global-equality

    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 zhijing-jin/nlp-phd-global-equality in production, what risks or prerequisites should they evaluate first?
    pass
    AI 明确点名了 zhijing-jin/nlp-phd-global-equality

    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 zhijing-jin/nlp-phd-global-equality solve, and who is the primary audience?
    pass
    AI 未点名 zhijing-jin/nlp-phd-global-equality —— 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?

嵌入你的 GEO 徽章

把这个徽章贴进 zhijing-jin/nlp-phd-global-equality 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。

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订阅 Pro,解锁深度诊断

zhijing-jin/nlp-phd-global-equality — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。

  • 深度报告每月 10 次
  • 无品牌品类查询5,轻量 2
  • 优先行动项8,轻量 3