SACL

The official repository for ACL 2023 paper "Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations". This paper proposes a supervised adversarial contrastive learning (SACL) framework for learning class-spread structured representations in a supervised manner, and demonstrate the effectiveness of SACL in context-dependent classification scenarios (i.e., ERC). Refer to the directory SACL-LSTM for the codes.

Additionally, the effectiveness of SACL in context-free classification scenarios (i.e., LSA) is demonstrated in its sister work, "UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis", which will be presented at SemEval@ACL 2023. Refer to the directory SACL-XLMR for the codes.

Citation

If you are interested in this work, and want to use the codes in this repo, please star this repo and cite by:

@inproceedings{DBLP:conf/acl/0001BWZH23,
  author       = {Dou Hu and
                  Yinan Bao and
                  Lingwei Wei and
                  Wei Zhou and
                  Songlin Hu},
  title        = {Supervised Adversarial Contrastive Learning for Emotion Recognition
                  in Conversations},
  booktitle    = {{ACL} {(1)}},
  pages        = {10835--10852},
  publisher    = {Association for Computational Linguistics},
  year         = {2023}
}

@inproceedings{DBLP:conf/semeval/0001WLZH23,
  author       = {Dou Hu and
                  Lingwei Wei and
                  Yaxin Liu and
                  Wei Zhou and
                  Songlin Hu},
  title        = {{UCAS-IIE-NLP} at SemEval-2023 Task 12: Enhancing Generalization of
                  Multilingual {BERT} for Low-resource Sentiment Analysis},
  booktitle    = {SemEval@ACL},
  pages        = {1849--1857},
  publisher    = {Association for Computational Linguistics},
  year         = {2023}
}