RRepoGEO

REPOGEO REPORT · LITE

km1994/nlp_paper_study

Default branch master · commit a40009f6 · scanned 6/26/2026, 7:07:54 PM

GitHub: 4,029 stars · 645 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface km1994/nlp_paper_study, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README H1 to clearly state the repo's purpose

    Why:

    CURRENT
    # 【关于 NLP】 那些你不知道的事
    COPY-PASTE FIX
    # NLP 顶会论文研读笔记与代码复现
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the content of the MIT License.
  • mediumtopics#3
    Expand repository topics to include resource type

    Why:

    CURRENT
    attention, bert, entity-recognition, gcn, relation-extraction
    COPY-PASTE FIX
    attention, bert, entity-recognition, gcn, relation-extraction, nlp-paper-study, research-notes, nlp-algorithms, deep-learning-nlp, paper-review

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface km1994/nlp_paper_study
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Speech and Language Processing
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Speech and Language Processing · recommended 1×
  2. Deep Learning for NLP · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. Neural Network Methods in Natural Language Processing · recommended 1×
  5. Papers With Code · recommended 1×
  • CATEGORY QUERY
    I need comprehensive study guides for state-of-the-art NLP algorithms and research.
    you: not recommended
    AI recommended (in order):
    1. Speech and Language Processing
    2. Deep Learning for NLP
    3. Hugging Face Transformers (huggingface/transformers)
    4. Neural Network Methods in Natural Language Processing
    5. Papers With Code
    6. ArXiv

    AI recommended 6 alternatives but never named km1994/nlp_paper_study. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking detailed explanations and code for advanced NLP topics like GCN and BERT.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library
    2. PyTorch Geometric (PyG)
    3. Stanford NLP (CoreNLP)
    4. Deep Graph Library (DGL)
    5. Keras (with TensorFlow)
    6. AllenNLP

    AI recommended 6 alternatives but never named km1994/nlp_paper_study. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of km1994/nlp_paper_study?
    pass
    AI named km1994/nlp_paper_study explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts km1994/nlp_paper_study in production, what risks or prerequisites should they evaluate first?
    pass
    AI named km1994/nlp_paper_study explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo km1994/nlp_paper_study solve, and who is the primary audience?
    pass
    AI did not name km1994/nlp_paper_study — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of km1994/nlp_paper_study. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/km1994/nlp_paper_study.svg)](https://repogeo.com/en/r/km1994/nlp_paper_study)
HTML
<a href="https://repogeo.com/en/r/km1994/nlp_paper_study"><img src="https://repogeo.com/badge/km1994/nlp_paper_study.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

km1994/nlp_paper_study — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite