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MLRoBERTa (RoBERTa pretrained on ML Papers)

How to use:

from transformers import AutoTokenizer, AutoModel
tok = AutoTokenizer.from_pretrained('shrutisingh/MLRoBERTa')
model = AutoModel.from_pretrained('shrutisingh/MLRoBERTa')

Pretraining Details:

This is a RoBERTa model trained on scientific documents. The dataset is composed of NeurIPS (1987-2019), CVPR (2013-2020), ICLR (2016-2020), ACL Anthology data (till 2019) paper title and abstracts, and ICLR paper reviews.

Citation:

@inproceedings{singh2021compare,
  title={COMPARE: a taxonomy and dataset of comparison discussions in peer reviews},
  author={Singh, Shruti and Singh, Mayank and Goyal, Pawan},
  booktitle={2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)},
  pages={238--241},
  year={2021},
  organization={IEEE}
}
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