Towards more equitable question answering systems: How much more data do you need?

Arnab Debnath, Navid Rajabi, Fardina Fathmiul Alam, Antonios Anastasopoulos. Towards more equitable question answering systems: How much more data do you need?. In Chengqing Zong, Fei Xia, Wenjie Li 0002, Roberto Navigli, editors, Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021, (Volume 2: Short Papers), Virtual Event, August 1-6, 2021. pages 621-629, Association for Computational Linguistics, 2021. [doi]

@inproceedings{DebnathRAA20,
  title = {Towards more equitable question answering systems: How much more data do you need?},
  author = {Arnab Debnath and Navid Rajabi and Fardina Fathmiul Alam and Antonios Anastasopoulos},
  year = {2021},
  url = {https://aclanthology.org/2021.acl-short.79},
  researchr = {https://researchr.org/publication/DebnathRAA20},
  cites = {0},
  citedby = {0},
  pages = {621-629},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021, (Volume 2: Short Papers), Virtual Event, August 1-6, 2021},
  editor = {Chengqing Zong and Fei Xia and Wenjie Li 0002 and Roberto Navigli},
  publisher = {Association for Computational Linguistics},
  isbn = {978-1-954085-53-4},
}