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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery (EMNLP'24)
| Date | Stars |
|---|---|
| 2026-07-31 | 661 |
| 2026-08-06 | 661 |
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# Awesome Scientific Language Models [](https://github.com/sindresorhus/awesome) [](https://img.shields.io/github/stars/yuzhimanhua/Awesome-Scientific-Language-Models?style=social) [](https://img.shields.io/badge/PaperNumber-296-blue) [](https://opensource.org/licenses/MIT) [](https://img.shields.io/badge/PRs-Welcome-red) A 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**). The repository is part of our survey paper [**A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery**](https://arxiv.org/abs/2406.10833) and will be continuously updated. **NOTE 1**: To avoid ambiguity, when we talk about the number of parameters in a model, "Base" refers to 110M (i.e., BERT-Base), and "Large" refers to 340M (i.e., BERT-Large). Other numbers will be written explicitly. **NOTE 2**: In each subsection, papers are sorted chronologically. If a paper has a preprint (e.g., arXiv or bioRxiv) version, its publication date is according to the preprint service. Otherwise, its publication date is according to the conference proceeding or journal. **NOTE 3**: We appreciate contributions. If you have any suggested papers, feel free to reach out to [email protected] or submit a [pull request](https://github.com/yuzhimanhua/Awesome-Scientific-Language-Models/pulls). For format consistency, we will include a paper after (1) it has a version with author names AND (2) its GitHub and/or Hugging Face links are available. <p align="center"> <img src="intro.svg" width="90%" style="align:center;"/> </p> ## Contents - [General](#general) - [Language](#general-language) - [Language + Graph](#general-language-graph) - [Mathematics](#mathematics) - [Language](#mathematics-language) - [Language + Vision](#mathematics-language-vision) - [Other Modalities (Table)](#mathematics-other-modalities-table) - [Physics](#physics) - [Language](#physics-language) - [Chemistry and Materials Science](#chemistry-and-materials-science) - [Language](#chemistry-language) - [Language + Graph](#chemistry-language-graph) - [Language + Vision](#chemistry-language-vision) - [Other Modalities (Molecule)](#chemistry-other-modalities-molecule) - [Biology and Medicine](#biology-and-medicine) - [Language](#biology-language) - [Language + Graph](#biology-language-graph) - [Language + Vision](#biology-language-vision) - [Other Modalities (Protein)](#biology-other-modalities-protein) - [Other Modalities (DNA)](#biology-other-modalities-dna) - [Other Modalities (RNA)](#biology-other-modalities-rna) - [Other Modalities (Multiomics)](#biology-other-modalities-multiomics) - [Geography, Geology, and Environmental Science](#geography-geology-and-environmental-science) - [Language](#geography-language) - [Language + Graph](#geography-language-graph) - [Language + Vision](#geography-language-vision) - [Other Modalities (Climate Time Series)](#geography-other-modalities-climate-time-series) ## General <h3 id="general-language">Language</h3> - **(SciBERT)** _SciBERT: A Pretrained Language Model for Scientific Text_ ```EMNLP 2019``` [[Paper](https://arxiv.org/abs/1903.10676)] [[GitHub](https://github.com/allenai/scibert)] [[Model (Base)](https://huggingface.c
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Bowen Jin · OpenAI · United States
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Rui Pan
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:2e588cc8a2135fbf, topic:large-language-models