FewshotQA: A simple framework for few-shot learning of question answering tasks using pre-trained text-to-text models

Rakesh Chada, Pradeep Natarajan. FewshotQA: A simple framework for few-shot learning of question answering tasks using pre-trained text-to-text models. In Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih, editors, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 7-11 November, 2021. pages 6081-6090, Association for Computational Linguistics, 2021. [doi]

@inproceedings{ChadaN21,
  title = {FewshotQA: A simple framework for few-shot learning of question answering tasks using pre-trained text-to-text models},
  author = {Rakesh Chada and Pradeep Natarajan},
  year = {2021},
  url = {https://aclanthology.org/2021.emnlp-main.491},
  researchr = {https://researchr.org/publication/ChadaN21},
  cites = {0},
  citedby = {0},
  pages = {6081-6090},
  booktitle = {Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 7-11 November, 2021},
  editor = {Marie-Francine Moens and Xuanjing Huang and Lucia Specia and Scott Wen-tau Yih},
  publisher = {Association for Computational Linguistics},
}