Exploration and Evaluation of Prompting Methods for Text Style Transfer

Author:

Stefan Vlad

Publisher

Springer Nature Switzerland

Reference23 articles.

1. Banerjee, S., Lavie, A.: METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization, pp. 65–72. Association for Computational Linguistics, Ann Arbor, Michigan (2005). https://aclanthology.org/W05-0909

2. Brown, T.B., et al.: Language models are few-shot learners. CoRR abs/2005.14165 (2020). https://arxiv.org/abs/2005.14165

3. Cao, Y., Shui, R., Pan, L., Kan, M., Liu, Z., Chua, T.: Expertise style transfer: a new task towards better communication between experts and laymen. CoRR abs/2005.00701 (2020). https://arxiv.org/abs/2005.00701

4. Cui, L., Wu, Y., Liu, J., Yang, S., Zhang, Y.: Template-based named entity recognition using BART. CoRR abs/2106.01760 (2021). https://arxiv.org/abs/2106.01760

5. Devlin, J., Chang, M., Lee, K., Toutanova, K.: BERT: pre-training of deep bidirectional transformers for language understanding. CoRR abs/1810.04805 (2018). http://arxiv.org/abs/1810.04805

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