🧑‍🔬 Saku Sugawara

🏛️ Affiliations

🔬National Institute of InformaticsTokyo · Japan2020–2026 · 54 paperscurrent🎓The University of TokyoTokyo · Japan2016–2026 · 19 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 more institutions on single bylines are not listed.

🧭 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps (2020 · 735 citations)
   Multi-hop QA benchmarks are meant to test whether a model can chain facts across several paragraphs. Earlier datasets either give no account of how an answer is reached or explain it only through flagged supporting sentences, and many of their questions can be solved with a single lookup. The authors present…
2. What Makes Reading Comprehension Questions Easier? (2018 · 178 citations)
   Machine reading comprehension (MRC) benchmarks are meant to test language understanding, but many of their questions may be solvable through shallow shortcuts.
3. Embracing Ambiguity: Shifting the Training Target of NLI Models (2021 · 36 citations)
   NLI benchmarks contain many pairs where annotators disagree, yet models are usually trained on a single gold label.

All works

6 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning StepsInternational Conference on Computational Linguistics (COLING)Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, et al.2020 · 735 citations
2. What Makes Reading Comprehension Questions Easier?Conference on Empirical Methods in Natural Language Processing (EMNLP)Saku Sugawara, Kentaro Inui, Satoshi Sekine, et al.2018 · 178 citations
3. Embracing Ambiguity: Shifting the Training Target of NLI ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Johannes Mario Meissner, Napat Thumwanit, Saku Sugawara, et al.2021 · 36 citations
4. Specification-Aware Machine Translation and Evaluation for Purpose Alignment ↗Proceedings of the Tenth Conference on Machine Translation · no summary yetYoko Kayano, Saku Sugawara2025 · 3 citations
5. PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments ↗Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL) · no summary yetDaiki Asami, Saku Sugawara2023 · 3 citations
6. Label Effects: Shared Heuristic Reliance in Trust Assessment by Humans and LLM-as-a-Judge ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetXin Sun et al.2026 · 1 citation

🤝 Co-authors here

3 co-authors with a page, the most papers together first.

• Akiko Aizawa ×3
• Kentaro Inui
• Satoshi Sekine

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2021
• International Conference on Computational Linguistics (COLING): COLING 2020
• Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2018
• Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
• Proceedings of the Tenth Conference on Machine Translation

🔗 Cited by

Papers of our library cite their works 583 times (of the 141,840 papers whose bibliographies we read); 41 citing papers with a page here →.

Updated 24 October 2026

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