REPOGEO REPORT · LITE
yuzhimanhua/Awesome-Scientific-Language-Models
Default branch main · commit dd5e953c · scanned 6/2/2026, 10:43:03 PM
GitHub: 660 stars · 39 forks
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 yuzhimanhua/Awesome-Scientific-Language-Models, 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.
- highreadme#1Reposition README opening to explicitly state 'awesome list' and 'survey' nature
Why:
CURRENTA curated list of pre-trained language models in scientific domains (e.g., **mathematics**, **physics**, **chemistry**, **materials science**, **biology**, **medicine**, **geoscience**), covering different model sizes (from **100M** to **100B parameters**) and modalities (e.g., **language**, **graph**, **vision**, **table**, **molecule**, **protein**, **genome**, **climate time series**).
COPY-PASTE FIXThis repository is **Awesome Scientific Language Models**, a comprehensive, curated **awesome list** and **survey** of pre-trained language models in scientific domains (e.g., **mathematics**, **physics**, **chemistry**, **materials science**, **biology**, **medicine**, **geoscience**). It covers different model sizes (from **100M** to **100B parameters**) and modalities (e.g., **language**, **graph**, **vision**, **table**, **molecule**, **protein**, **genome**, **climate time series**).
- mediumtopics#2Add 'awesome-list' to repository topics
Why:
CURRENTai4science, awesome-resources, large-language-models, scientific-text-mining, survey
COPY-PASTE FIXai4science, awesome-resources, awesome-list, large-language-models, scientific-text-mining, survey
- mediumreadme#3Add a 'Why this list?' section to highlight differentiators
Why:
COPY-PASTE FIX## Why Awesome Scientific Language Models? Unlike general-purpose LLM lists or those focused on a single scientific field (e.g., biomedical), this repository provides a uniquely curated and comprehensive overview of Language Models specifically applied across diverse **scientific domains** such as mathematics, physics, chemistry, materials science, biology, medicine, and geoscience.
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.
- Hugging Face Models · recommended 1×
- Papers With Code · recommended 1×
- arXiv · recommended 1×
- Google Scholar · recommended 1×
- BioNLP Shared Tasks · recommended 1×
- CATEGORY QUERYWhere can I find a comprehensive list of large language models for scientific research?you: not recommendedAI recommended (in order):
- Hugging Face Models
- Papers With Code
- arXiv
- Google Scholar
- BioNLP Shared Tasks
- ChemNLP
- Materials Project
- Towards Data Science
- SyncedReview
- ChatGPT
- GPT-4
AI recommended 11 alternatives but never named yuzhimanhua/Awesome-Scientific-Language-Models. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat are the best pre-trained language models for chemistry or biology applications?you: not recommendedAI recommended (in order):
- ChemBERTa-2
- BioMegatron
- PubMedBERT
- MolFormer
- SciBERT
- ESM-2
AI recommended 6 alternatives but never named yuzhimanhua/Awesome-Scientific-Language-Models. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesspass
- README presencepass
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 yuzhimanhua/Awesome-Scientific-Language-Models?passAI did not name yuzhimanhua/Awesome-Scientific-Language-Models — 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 yuzhimanhua/Awesome-Scientific-Language-Models in production, what risks or prerequisites should they evaluate first?passAI named yuzhimanhua/Awesome-Scientific-Language-Models 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 yuzhimanhua/Awesome-Scientific-Language-Models solve, and who is the primary audience?passAI did not name yuzhimanhua/Awesome-Scientific-Language-Models — 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
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yuzhimanhua/Awesome-Scientific-Language-Models — 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