RRepoGEO

REPOGEO REPORT · LITE

thunlp/TAADpapers

Default branch master · commit fbd155c8 · scanned 6/19/2026, 10:07:20 PM

GitHub: 1,574 stars · 194 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)

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

AI VISIBILITY SCORE
22 /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
1 / 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 thunlp/TAADpapers, 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's opening to emphasize its curated nature

    Why:

    CURRENT
    # Must-read Papers on Textual Adversarial Attack and Defense (TAAD)

This list is currently maintained by Chenghao Yang at UChicago.
    COPY-PASTE FIX
    # Must-read Papers on Textual Adversarial Attack and Defense (TAAD)

This repository provides a **curated and organized list of essential research papers** on Textual Adversarial Attack and Defense (TAAD). It is currently maintained by Chenghao Yang at UChicago.
  • mediumtopics#2
    Add more specific topics to reinforce 'curated list' and 'research'

    Why:

    CURRENT
    adversarial-attacks, adversarial-defense, adversarial-learning, natural-language-processing, nlp, paper-list
    COPY-PASTE FIX
    adversarial-attacks, adversarial-defense, adversarial-learning, natural-language-processing, nlp, paper-list, nlp-research, research-papers, curated-list
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/thunlp/TAADpapers

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 thunlp/TAADpapers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TextAttack
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. TextAttack · recommended 1×
  2. OpenAttack · recommended 1×
  3. WordNet · recommended 1×
  4. Word2Vec · recommended 1×
  5. GloVe · recommended 1×
  • CATEGORY QUERY
    What techniques exist for creating adversarial text examples to test NLP model robustness?
    you: not recommended
    AI recommended (in order):
    1. TextAttack
    2. OpenAttack
    3. WordNet
    4. Word2Vec
    5. GloVe
    6. FastText
    7. BERT
    8. Adversarial GLUE
    9. T5
    10. BART
    11. Pegasus
    12. CheckList
    13. GPT-3.5
    14. GPT-4
    15. Google Translate
    16. DeepL

    AI recommended 16 alternatives but never named thunlp/TAADpapers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find research papers on defending NLP systems against textual adversarial attacks?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. ACL Anthology
    4. Semantic Scholar
    5. Microsoft Academic
    6. DBLP Computer Science Bibliography

    AI recommended 6 alternatives but never named thunlp/TAADpapers. 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 thunlp/TAADpapers?
    pass
    AI did not name thunlp/TAADpapers — 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?

  • If a team adopts thunlp/TAADpapers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named thunlp/TAADpapers 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 thunlp/TAADpapers solve, and who is the primary audience?
    pass
    AI did not name thunlp/TAADpapers — 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 thunlp/TAADpapers. 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/thunlp/TAADpapers.svg)](https://repogeo.com/en/r/thunlp/TAADpapers)
HTML
<a href="https://repogeo.com/en/r/thunlp/TAADpapers"><img src="https://repogeo.com/badge/thunlp/TAADpapers.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

thunlp/TAADpapers — 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