Papers by Yuya Asano
Contextual ASR Error Handling with LLMs Augmentation for Goal-Oriented Conversational AI (2025.coling-industry)
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Yuya Asano, Sabit Hassan, Paras Sharma, Anthony B. Sicilia, Katherine Atwell, Diane Litman, Malihe Alikhani
| Challenge: | Existing ASR correction methods rely on prior user data or named entities . Existing methods based on prior data are not available for goal-oriented dialogues . |
| Approach: | They propose a method that integrates contextual information from the dialogue states of a goal-oriented conversational AI and its tasks into a large language model. |
| Outcome: | The proposed method improves recall and F1 of correction by 34% and 16% while maintaining precision and false positive rate. |
Can LLMs simulate the same correct solutions to free-response math problems as real students? (2025.emnlp-main)
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| Challenge: | Existing studies have explored modeling student mistakes, but lack of understanding of how they generate correct solutions. |
| Approach: | They compare distribution of correct solutions produced by four large language models with students' responses to free-response problems. |
| Outcome: | The proposed model can generate correct solutions that represent student responses to free-response problems. |