RRepoGEO

REPOGEO REPORT · LITE

AspirinCode/papers-for-molecular-design-using-DL

Default branch main · commit 0a891df1 · scanned 6/7/2026, 2:23:09 AM

GitHub: 941 stars · 118 forks

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 AspirinCode/papers-for-molecular-design-using-DL, 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
    Clarify the repository's nature as a paper list in the README's opening

    Why:

    CURRENT
    related to **Generative AI** and **Deep Learning** for **molecular/drug design** and **molecular conformation generation**.
    COPY-PASTE FIX
    This repository provides a curated and actively updated list of research papers focused on **Generative AI** and **Deep Learning** for **molecular/drug design** and **molecular conformation generation**.
  • mediumhomepage#2
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add a relevant URL to the "Homepage" field in the repository's "About" section. For example, `https://github.com/AspirinCode/papers-for-molecular-design-using-DL` or a dedicated project page if one exists.
  • lowreadme#3
    Remove informal and unclear statements from the README

    Why:

    CURRENT
    Updating ...
    
    ## Molecular Optimization
    Molecular Optimization will welcome !!!
    COPY-PASTE FIX
    Remove "Updating ..." and "Molecular Optimization will welcome !!!".

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 AspirinCode/papers-for-molecular-design-using-DL
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AlphaFold2/AlphaFold3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. AlphaFold2/AlphaFold3 · recommended 1×
  2. MolGAN · recommended 1×
  3. REINVENT · recommended 1×
  4. Junction Tree VAE (JT-VAE) · recommended 1×
  5. GCPN · recommended 1×
  • CATEGORY QUERY
    How to apply deep generative models for novel drug discovery and molecular design?
    you: not recommended
    AI recommended (in order):
    1. AlphaFold2/AlphaFold3
    2. MolGAN
    3. REINVENT
    4. Junction Tree VAE (JT-VAE)
    5. GCPN
    6. FEP+
    7. Ligand Designer
    8. GPT-3/GPT-4

    AI recommended 8 alternatives but never named AspirinCode/papers-for-molecular-design-using-DL. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking research papers on generative AI methods for material science and compound synthesis.
    you: not recommended
    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 AspirinCode/papers-for-molecular-design-using-DL?
    pass
    AI did not name AspirinCode/papers-for-molecular-design-using-DL — 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 AspirinCode/papers-for-molecular-design-using-DL in production, what risks or prerequisites should they evaluate first?
    pass
    AI named AspirinCode/papers-for-molecular-design-using-DL 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 AspirinCode/papers-for-molecular-design-using-DL solve, and who is the primary audience?
    pass
    AI did not name AspirinCode/papers-for-molecular-design-using-DL — 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?

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AspirinCode/papers-for-molecular-design-using-DL — 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