Papers by Masaki Uto

2 papers
Analytic Automated Essay Scoring Based on Deep Neural Networks Integrating Multidimensional Item Response Theory (2022.coling-1)

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Challenge: Essay exams have two drawbacks in that grading them is expensive and raises questions about fairness.
Approach: They propose to use a multidimensional item response theory model to improve interpretability while maintaining scoring accuracy.
Outcome: The proposed model improves interpretability while maintaining accuracy while preserving cost and accuracy.
Neural Automated Essay Scoring Incorporating Handcrafted Features (2020.coling-main)

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Challenge: Automated essay scoring (AES) relies on handcrafted features, but recent studies have proposed a hybrid method that integrates handcrafted essay-level features into a DNN-AES model.
Approach: They propose a method that integrates handcrafted features into a DNN-AES model.
Outcome: The proposed method significantly improves the accuracy of existing methods.

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