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Ayaka Suzuki
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2020 – today
- 2024
- [j1]Yuto Tomikawa, Ayaka Suzuki, Masaki Uto:
Adaptive Question-Answer Generation With Difficulty Control Using Item Response Theory and Pretrained Transformer Models. IEEE Trans. Learn. Technol. 17: 2240-2252 (2024) - [c4]Yuri Sato, Ayaka Suzuki, Koji Mineshima:
Building a Large Dataset of Human-Generated Captions for Science Diagrams. Diagrams 2024: 393-401 - [c3]Masaki Uto, Yuto Tomikawa, Ayaka Suzuki:
Question Difficulty Prediction Based on Virtual Test-Takers and Item Response Theory. EcalLAC@AIED 2024 - 2023
- [c2]Masaki Uto, Yuto Tomikawa, Ayaka Suzuki:
Difficulty-Controllable Neural Question Generation for Reading Comprehension using Item Response Theory. BEA@ACL 2023: 119-129 - 2020
- [i1]Ayaka Suzuki, Yoshiro Suzuki:
Deep learning achieves perfect anomaly detection on 108, 308 retinal images including unlearned diseases. CoRR abs/2001.05859 (2020)
2010 – 2019
- 2013
- [c1]Anna Noguchi, Toshifumi Kurosawa, Ayaka Suzuki, Yuichiro Sakamoto, Tatsuhito Oe, Takuto Yoshikawa, Buntarou Shizuki, Jiro Tanaka:
Evaluation of a Soft-Surfaced Multi-touch Interface. HCI (4) 2013: 469-478
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last updated on 2024-12-02 22:26 CET by the dblp team
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