13 citations · 13 across the 5 of their papers we have counts for
5 papers
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…
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…
Assessing Step-by-Step Reasoning against Lexical Negation: A Case Study on Syllogism
Mengyu Ye, Tatsuki Kuribayashi, Jun Suzuki +2
Large language models (LLMs) take advantage of step-by-step reasoning instructions, e.g., chain-of-thought (CoT) prompting. Building on this, their ability to perform CoT-style rea…
Balancing Cost and Quality: An Exploration of Human-in-the-loop Frameworks for Automated Short Answer Scoring
Hiroaki Funayama, Tasuku Sato, Yuichiroh Matsubayashi +3
Short answer scoring (SAS) is the task of grading short text written by a learner. In recent years, deep-learning-based approaches have substantially improved the performance of SA…