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Yuya Asano

2 accepted papers

2025

Can LLMs simulate the same correct solutions to free-response math problems as real students?

EMNLP 2025

Large language models (LLMs) have emerged as powerful tools for developing educational systems. While previous studies have explored modeling student mistakes, a critical gap remains in understanding whether LLMs can generate correct solutions that represent student responses to free-response proble

Cited by 0SourcePDFScholar
2025

Contextual ASR Error Handling with LLMs Augmentation for Goal-Oriented Conversational AI

COLING 2025industry

General-purpose automatic speech recognition (ASR) systems do not always perform well in goal-oriented dialogue. Existing ASR correction methods rely on prior user data or named entities. We extend correction to tasks that have no prior user data and exhibit linguistic flexibility such as lexical an…