| Multiple choice question generation utilizing an ontology K Stasaski, MA Hearst Proceedings of the 12th Workshop on Innovative Use of NLP for Building …, 2017 | 75 | 2017 |
| Automatically generating cause-and-effect questions from passages K Stasaski, M Rathod, T Tu, Y Xiao, MA Hearst Proceedings of the 16th workshop on innovative use of NLP for building …, 2021 | 26 | 2021 |
| CIMA: A large open access dialogue dataset for tutoring K Stasaski, K Kao, MA Hearst Proceedings of the Fifteenth Workshop on Innovative Use of NLP for Building …, 2020 | 24 | 2020 |
| Educational multi-question generation for reading comprehension M Rathod, T Tu, K Stasaski Proceedings of the 17th Workshop on Innovative Use of NLP for Building …, 2022 | 18 | 2022 |
| Semantic diversity in dialogue with natural language inference K Stasaski, MA Hearst arXiv preprint arXiv:2205.01497, 2022 | 16 | 2022 |
| More diverse dialogue datasets via diversity-informed data collection K Stasaski, GH Yang, MA Hearst Proceedings of the 58th annual meeting of the association for computational …, 2020 | 16 | 2020 |
| Exploring the impact of gender bias on pair programming A Akalin, N Weinman, K Stasaski, A Fox Proceedings of the 17th ACM conference on international computing education …, 2021 | 4 | 2021 |
| Automatic feedback generation for dialog-based language tutors using transformer models and active learning K Stasaski, V Ramanarayanan 34th Conference on Neural Information Processing Systems, Vancouver, 2020 | 3 | 2020 |
| Pragmatically appropriate diversity for dialogue evaluation K Stasaski, MA Hearst arXiv preprint arXiv:2304.02812, 2023 | 2 | 2023 |
| Diversity in Dialogue Generation KR Stasaski University of California, Berkeley, 2022 | | 2022 |
| Supplementary Material for Multiple Choice Question Generation Utilizing An Ontology K Stasaski, M Hearst | | |
