A Survey of Machine Narrative Reading Comprehension Assessments

Abstract

As the body of research on machine narrative comprehension grows, there is a critical need for consideration of performance assessment strategies as well as the depth and scope of different benchmark tasks. Based on narrative theories, reading comprehension theories, as well as existing machine narrative reading comprehension tasks and datasets, we propose a typology that captures the main similarities and differences among assessment tasks; and discuss the implications of our typology for new task design and the challenges of narrative reading comprehension.

Cite

Text

Sang et al. "A Survey of Machine Narrative Reading Comprehension Assessments." International Joint Conference on Artificial Intelligence, 2022. doi:10.24963/IJCAI.2022/779

Markdown

[Sang et al. "A Survey of Machine Narrative Reading Comprehension Assessments." International Joint Conference on Artificial Intelligence, 2022.](https://mlanthology.org/ijcai/2022/sang2022ijcai-survey/) doi:10.24963/IJCAI.2022/779

BibTeX

@inproceedings{sang2022ijcai-survey,
  title     = {{A Survey of Machine Narrative Reading Comprehension Assessments}},
  author    = {Sang, Yisi and Mou, Xiangyang and Li, Jing and Stanton, Jeffrey M. and Yu, Mo},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {5580-5587},
  doi       = {10.24963/IJCAI.2022/779},
  url       = {https://mlanthology.org/ijcai/2022/sang2022ijcai-survey/}
}