13 citations · 21 across the 6 of their papers we have counts for
9 papers
Tell Me Who Your Students Are: GPT Can Generate Valid Multiple-Choice Questions When Students' (Mis)Understanding Is Hinted
Machi Shimmei, Masaki Uto, Yuichiroh Matsubayashi +3
The primary goal of this study is to develop and evaluate an innovative prompting technique, AnaQuest, for generating multiple-choice questions (MCQs) using a pre-trained large lan…
Automatic Feedback Generation for Short Answer Questions using Answer Diagnostic Graphs
Momoka Furuhashi, Hiroaki Funayama, Yuya Iwase +5
Short-reading comprehension questions help students understand text structure but lack effective feedback. Students struggle to identify and correct errors, while manual feedback c…
Reducing the Cost: Cross-Prompt Pre-Finetuning for Short Answer Scoring
Hiroaki Funayama, Yuya Asazuma, Yuichiroh Matsubayashi +2
Automated Short Answer Scoring (SAS) is the task of automatically scoring a given input to a prompt based on rubrics and reference answers. Although SAS is useful in real-world app…
To Drop or Not to Drop? Predicting Argument Ellipsis Judgments: A Case Study in Japanese
Yukiko Ishizuki, Tatsuki Kuribayashi, Yuichiroh Matsubayashi +2
Speakers sometimes omit certain arguments of a predicate in a sentence; such omission is especially frequent in pro-drop languages. This study addresses a question about ellipsis -…
Japanese-English Sentence Translation Exercises Dataset for Automatic Grading
Naoki Miura, Hiroaki Funayama, Seiya Kikuchi +3
This paper proposes the task of automatic assessment of Sentence Translation Exercises (STEs), that have been used in the early stage of L2 language learning. We formalize the task…
Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution
Ryuto Konno, Shun Kiyono, Yuichiroh Matsubayashi +2
Masked language models (MLMs) have contributed to drastic performance improvements with regard to zero anaphora resolution (ZAR). To further improve this approach, in this study, w…