| Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps X Ho, AKD Nguyen, S Sugawara, A Aizawa Proceedings of the 28th International Conference on Computational …, 2020 | 172 | 2020 |
| What Makes Reading Comprehension Questions Easier? S Sugawara, K Inui, S Sekine, A Aizawa Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 138 | 2018 |
| Assessing the benchmarking capacity of machine reading comprehension datasets S Sugawara, P Stenetorp, K Inui, A Aizawa Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 8918-8927, 2020 | 80 | 2020 |
| Evaluation metrics for machine reading comprehension: Prerequisite skills and readability S Sugawara, Y Kido, H Yokono, A Aizawa Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 44 | 2017 |
| What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks? N Nangia, S Sugawara, H Trivedi, A Warstadt, C Vania, SR Bowman Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 29 | 2021 |
| Prerequisite skills for reading comprehension: Multi-perspective analysis of mctest datasets and systems S Sugawara, H Yokono, A Aizawa Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 23 | 2017 |
| Embracing Ambiguity: Shifting the Training Target of NLI Models JM Meissner, N Thumwanit, S Sugawara, A Aizawa Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 22 | 2021 |
| Benchmarking Machine Reading Comprehension: A Psychological Perspective S Sugawara, P Stenetorp, A Aizawa Proceedings of the 16th Conference of the European Chapter of the …, 2021 | 19* | 2021 |
| Improving the Robustness of QA Models to Challenge Sets with Variational Question-Answer Pair Generation K Shinoda, S Sugawara, A Aizawa Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021 | 16* | 2021 |
| An analysis of prerequisite skills for reading comprehension S Sugawara, A Aizawa Proceedings of the Workshop on Uphill Battles in Language Processing …, 2016 | 15 | 2016 |
| Debiasing Masks: A New Framework for Shortcut Mitigation in NLU JM Meissner, S Sugawara, A Aizawa Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022 | 13 | 2022 |
| What Makes Reading Comprehension Questions Difficult? S Sugawara, N Nangia, A Warstadt, SR Bowman Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 13 | 2022 |
| Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical Overlap K Shinoda, S Sugawara, A Aizawa Proceedings of the 3rd Workshop on Machine Reading for Question Answering, 63-72, 2021 | 10 | 2021 |
| Improving translation of case descriptions into logical fact formulas using LegalCaseNER MM Zin, HT Nguyen, K Satoh, S Sugawara, F Nishino Proceedings of the Nineteenth International Conference on Artificial …, 2023 | 8 | 2023 |
| Look to the Right: Mitigating Relative Position Bias in Extractive Question Answering K Shinoda, S Sugawara, A Aizawa Proceedings of the fifth BlackboxNLP Workshop on Analyzing and Interpreting …, 2022 | 7 | 2022 |
| A survey on measuring and mitigating reasoning shortcuts in machine reading comprehension X Ho, JM Meissner, S Sugawara, A Aizawa arXiv preprint arXiv:2209.01824, 2022 | 7 | 2022 |
| Probing Physical Reasoning with Counter-Commonsense Context K Kondo, S Sugawara, A Aizawa Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 6 | 2023 |
| Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question Answering X Ho, AKD Nguyen, S Sugawara, A Aizawa Findings of the Association for Computational Linguistics: EACL 2023, 2023 | 6 | 2023 |
| Which Shortcut Solution Do Question Answering Models Prefer to Learn? K Shinoda, S Sugawara, A Aizawa Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023 | 5 | 2023 |
| Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios M Ashida, S Sugawara Proceedings of the 29th International Conference on Computational …, 2022 | 5 | 2022 |
