Papers by Yutaro Shigeto
Rethinking Loss Functions for Fact Verification (2024.eacl-short)
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| Challenge: | Existing objective functions for fact verification fail to capture heterogeneity among verdict classes . cross-entropy loss treats all misclassification types uniformly, which is problematic . |
| Approach: | They propose two task-specific objective functions that capture the heterogeneity among verdict classes . they use a dictionary-based objective function to classify Wikipedia sentences into three verdict classes. |
| Outcome: | The proposed objectives outperform the standard cross-entropy loss objective . the proposed objectives are combined with simple class weighting to overcome imbalance . |
Video Caption Dataset for Describing Human Actions in Japanese (2020.lrec-1)
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| Challenge: | Existing video caption datasets for English have no equivalent for Japanese . authors evaluated two methods to obtain benchmark results . |
| Approach: | They propose to use Japanese video captions to describe human actions . they evaluated two different methods to obtain benchmark results . |
| Outcome: | The proposed dataset evaluates two different methods to obtain benchmark results . it shows that the generation methods can specify "who does what and where" |