Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
text
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
climate
License:
Update README.md
Browse files
README.md
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@@ -36,8 +36,8 @@ by using a seed set of climate-related keywords. The abstracts were annotated by
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### Dataset Sources
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- **Source
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- **Paper:**
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## Uses
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## Citation
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The source data has been fetched from the Semantic Scholar Academic Graph Datasets ("abstracts" dataset).
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This collection is licensed under [ODC-BY](https://opendatacommons.org/licenses/by/1.0/).
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By downloading this data you acknowledge that you have read and agreed to all the terms in this license.
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When using this data in a product or service, or including data in a redistribution, please cite the following paper:
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**BibTeX:**
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```
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@misc{https://doi.org/10.48550/arxiv.2301.10140,
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title = {The Semantic Scholar Open Data Platform},
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### Dataset Sources
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- **Source:** A subset of [Semantic Scholar Academic Graph Dataset](https://arxiv.org/abs/2301.10140) (the "abstracts" dataset)
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- **Paper:** [INDUS: Effective and Efficient Language Models for Scientific Applications](https://arxiv.org/abs/2405.10725)
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## Uses
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## Citation
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**BibTeX:**
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When using this data, please cite the following paper:
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```
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@misc{bhattacharjee2024indus,
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title={INDUS: Effective and Efficient Language Models for Scientific Applications},
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author={Bishwaranjan Bhattacharjee and Aashka Trivedi and Masayasu Muraoka and Muthukumaran Ramasubramanian and Takuma Udagawa and Iksha Gurung and Rong Zhang and Bharath Dandala and Rahul Ramachandran and Manil Maskey and Kayleen Bugbee and Mike Little and Elizabeth Fancher and Lauren Sanders and Sylvain Costes and Sergi Blanco-Cuaresma and Kelly Lockhart and Thomas Allen and Felix Grazes and Megan Ansdel and Alberto Accomazzi and Yousef El-Kurdi and Davis Wertheimer and Birgit Pfitzmann and Cesar Berrospi Ramis and Michele Dolfi and Rafael Teixeira de Lima and Panos Vagenas and S. Karthik Mukkavilli and Peter Staar and Sanaz Vahidinia and Ryan McGranaghan and Armin Mehrabian and Tsendgar Lee},
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year={2024},
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eprint={2405.10725},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2405.10725}
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}
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```
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The source data has been fetched from the Semantic Scholar Academic Graph Datasets ("abstracts" dataset).
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This collection is licensed under [ODC-BY](https://opendatacommons.org/licenses/by/1.0/).
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By downloading this data you acknowledge that you have read and agreed to all the terms in this license.
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When using this data in a product or service, or including data in a redistribution, please cite the following paper:
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```
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@misc{https://doi.org/10.48550/arxiv.2301.10140,
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title = {The Semantic Scholar Open Data Platform},
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