Papers by Kohei Tsuji

2 papers
SubRegWeigh: Effective and Efficient Annotation Weighing with Subword Regularization (2025.coling-main)

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Challenge: Existing methods to reduce the adverse effect of annotation errors are time-consuming because they require many trained models to detect errors.
Approach: They propose a method that uses a tokenization technique called subword regularization to simulate multiple error detection models for detecting errors.
Outcome: The proposed method performs weighting weighting four to five times faster than existing methods and improves in document classification and named entity recognition tasks.
Investigating Neurons and Heads in Transformer-based LLMs for Typographical Errors (2025.emnlp-main)

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Challenge: Existing studies have focused on surface-level display of performance degradation due to typos.
Approach: They propose a method to identify typo neurons and typo heads that work actively when inputs contain typos.
Outcome: The proposed method identifies typo neurons and typo heads that work actively when inputs contain typos.

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