https://github.com/lfoppiano/mining-llm-evaluation-paper
Source of the article "Mining experimental data from Materials Science literature with Large Language Models: an evaluation study"
https://github.com/lfoppiano/mining-llm-evaluation-paper
bert llm machine machine-learning materials materials-science tdm
Last synced: 6 months ago
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Source of the article "Mining experimental data from Materials Science literature with Large Language Models: an evaluation study"
- Host: GitHub
- URL: https://github.com/lfoppiano/mining-llm-evaluation-paper
- Owner: lfoppiano
- Created: 2023-12-13T11:40:20.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-15T08:27:53.000Z (almost 2 years ago)
- Last Synced: 2025-02-10T09:23:22.311Z (over 1 year ago)
- Topics: bert, llm, machine, machine-learning, materials, materials-science, tdm
- Language: TeX
- Homepage: https://www.tandfonline.com/doi/full/10.1080/27660400.2024.2356506
- Size: 1.13 MB
- Stars: 5
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Repository of the article
Foppiano, L., Lambard, G., Amagasa, T., & Ishii, M. (2024). Mining experimental data from materials science literature with large language models: an evaluation study. Science and Technology of Advanced Materials: Methods, 4(1). https://doi.org/10.1080/27660400.2024.2356506
Data and Code mentioned in the manuscript are available at [https://github.com/lfoppiano/MatSci-LuMEN](https://github.com/lfoppiano/MatSci-LumEn)
DOI: https://doi.org/10.1080/27660400.2024.2356506
To cite this work:
```bibtex
@article{doi:10.1080/27660400.2024.2356506,
title = {Mining experimental data from materials science literature with large language models: an evaluation study},
author = {Luca Foppiano, Guillaume Lambard, Toshiyuki Amagasa and Masashi Ishii},
year = 2024,
journal = {Science and Technology of Advanced Materials: Methods},
publisher = {Taylor \& Francis},
volume = 4,
number = 1,
pages = 2356506,
doi = {10.1080/27660400.2024.2356506},
url = {https://doi.org/10.1080/27660400.2024.2356506},
eprint = {https://doi.org/10.1080/27660400.2024.2356506}
}
```