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---
license: apache-2.0
task_categories:
- text-classification
- zero-shot-classification
language:
- en
size_categories:
- n<1K
---
> This benchmark is from the SciPrompt paper: https://huggingface.co/papers/2410.01946
`Emerging NLP` encompasses 21 newly developed research fields within the broader category of [Computation and Language](https://arxiv.org/list/cs.CL/recent).
We collect 30 examples for each topic, assigning five instances for training and another five for validation. The rest of the examples are used for testing. In total, we collect 210 for training and 420 for the test sets.
For detailed information regarding the dataset or SciPrompt framework, please refer to our [Github repo](https://github.com/zhiwenyou103/SciPrompt) and the [EMNLP paper](https://aclanthology.org/2024.emnlp-main.350.pdf).
## Citation Information
For the use of SciPrompt and Emerging NLP benchmark, please cite:
```bibtex
@inproceedings{you-etal-2024-sciprompt,
title = "{S}ci{P}rompt: Knowledge-augmented Prompting for Fine-grained Categorization of Scientific Topics",
author = "You, Zhiwen and
Han, Kanyao and
Zhu, Haotian and
Ludaescher, Bertram and
Diesner, Jana",
editor = "Al-Onaizan, Yaser and
Bansal, Mohit and
Chen, Yun-Nung",
booktitle = "Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2024",
address = "Miami, Florida, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.emnlp-main.350",
pages = "6087--6104",
}
```
## Contact Information
If you have any questions, please email `zhiweny2@illinois.edu`. |