Sugawara Saku 菅原朔

Researcher Number	10855894
Affiliation (Current)	2023: 国立情報学研究所, コンテンツ科学研究系, 助教
Affiliation (based on the past Project Information) *help	2020 – 2022: 国立情報学研究所, コンテンツ科学研究系, 助教
Review Section/Research Field	Principal Investigator 1001:Information science, computer engineering, and related fields / Basic Section 61030:Intelligent informatics-related
Keywords	Principal Investigator 自然言語処理 / 計算言語学 / 自然言語理解 / 言語理解 / 機械読解 / 質問応答 / 文章読解 / 談話理解

Constructing Reading Comprehension Datasets to Evaluate Discourse-level Language UnderstandingPrincipal Investigator
- Principal Investigator
  
  菅原朔
- Project Period (FY)
  2022 – 2024
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 61030:Intelligent informatics-related
- Research Institution
  National Institute of Informatics
Creating Auxiliary Questions for Explainable Evaluation of Machine Reading ComprehensionPrincipal Investigator
- Principal Investigator
  
  菅原朔
- Project Period (FY)
  2020 – 2022
- Research Category
  
  Grant-in-Aid for Research Activity Start-up
- Review Section
  
  1001:Information science, computer engineering, and related fields
- Research Institution
  National Institute of Informatics

All 2021

All Journal Article

[Journal Article] Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical Overlap.2021
- Author(s)
  Kazutoshi Shinoda, Saku Sugawara, Akiko Aizawa
- Journal Title
  
  The 3rd Workshop on Machine Reading for Question Answering (MRQA), at the 2021 conference on Empirical Methods in Natural Language Processing (EMNLP)
  
  Volume: - Pages: 63-72
- DOI
  10.18653/v1/2021.mrqa-1.6
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-21H03502, KAKENHI-PROJECT-20K23335
[Journal Article] Benchmarking Machine Reading Comprehension: A Psychological Perspective2021
- Author(s)
  Saku Sugawara, Pontus Stenetorp, Akiko Aizawa
- Journal Title
  
  Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
  
  Volume: 1 Pages: 1592-1612
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K23335
[Journal Article] Improving the Robustness of QA Models to Challenge Sets with Variational Question-Answer Pair Generation2021
- Author(s)
  Shinoda Kazutoshi、Sugawara Saku、Aizawa Akiko
- Journal Title
  
  Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop
  
  Volume: - Pages: 197-214
- DOI
  10.18653/v1/2021.acl-srw.21
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-20K23335

1. 相澤彰子

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

Sugawara Saku 菅原朔

Research Projects

Research Products

Co-Researchers

Constructing Reading Comprehension Datasets to Evaluate Discourse-level Language UnderstandingPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Creating Auxiliary Questions for Explainable Evaluation of Machine Reading ComprehensionPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical Overlap.2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Benchmarking Machine Reading Comprehension: A Psychological Perspective2021

Author(s)

Journal Title

Data Source

[Journal Article] Improving the Robustness of QA Models to Challenge Sets with Variational Question-Answer Pair Generation2021

Author(s)

Journal Title

DOI

Data Source

Sugawara Saku 菅原 朔

Research Projects

Research Products

Co-Researchers

Constructing Reading Comprehension Datasets to Evaluate Discourse-level Language UnderstandingPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Creating Auxiliary Questions for Explainable Evaluation of Machine Reading ComprehensionPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical Overlap.2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Benchmarking Machine Reading Comprehension: A Psychological Perspective2021

Author(s)

Journal Title

Data Source

[Journal Article] Improving the Robustness of QA Models to Challenge Sets with Variational Question-Answer Pair Generation2021

Author(s)

Journal Title

DOI

Data Source

Sugawara Saku 菅原朔