nibuhao/-

Official implementation of the TNNLS2022 work "Description-Enhanced Label Embedding Contrastive Learning for Text Classification"

DELE_pytorch

This is the official implementation of the TNNLS2022 work "Description-Enhanced Label Embedding Contrastive Learning for Text Classification"

Requirment

1. pytorch >= 1.7.1
2. photinia
3. Transformer

Data Preparation

1. SNLI [https://nlp.stanford.edu/projects/snli/]
2. SICK [https://huggingface.co/datasets/sick]
3. SciTail [https://allenai.org/data/scitail]
4. Quora Question Pair [https://huggingface.co/datasets/quora]
5. MSRP [https://www.microsoft.com/en-us/download/details.aspx?id=52398]
6. Yahoo Answer [https://huggingface.co/datasets/yahoo_answers_topics]
7. SST [https://nlp.stanford.edu/sentiment/treebank.html]

Note that most of the datasets can be obtained from the huggingface dataset

Bibtex

If you use this dataset or code in your work, please cite our paper:

@inproceedings{zhang2021making,
  title={Making the relation matters: Relation of relation learning network for sentence semantic matching},
  author={Zhang, Kun and Wu, Le and Lv, Guangyi and Wang, Meng and Chen, Enhong and Ruan, Shulan},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={35},
  number={16},
  pages={14411--14419},
  year={2021}
}