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Saku Sugawara
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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
1422020
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
1302018
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
762020
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
442017
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
282021
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
212017
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
202021
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
17*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
15*2021
An analysis of prerequisite skills for reading comprehension
S Sugawara, A Aizawa
Proceedings of the Workshop on Uphill Battles in Language Processing …, 2016
152016
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
122022
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
102022
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
102021
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
72022
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
62023
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
62023
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
62023
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
52023
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
52022
Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios
M Ashida, S Sugawara
Proceedings of the 29th International Conference on Computational …, 2022
42022
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Artikler 1–20