Papers by Jaeseo Lim
Devil’s Advocate: Novel Boosting Ensemble Method from Psychological Findings for Text Classification (2021.findings-emnlp)
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| Challenge: | Existing ensemble methods that combine submodels to create a composite model can improve model performance by diminishing model bias and variance. |
| Approach: | They propose a method which uses a deliberately dissenting model to force other submodels within the ensemble to better collaborate. |
| Outcome: | The proposed method shows comparable or improved performance on 5 text classification tasks when compared to conventional methods. |
Dual Attention Networks for Visual Reference Resolution in Visual Dialog (D19-1)
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| Challenge: | Visual dialog (VisDial) requires a dialog agent to answer a series of questions grounded in an image. |
| Approach: | They propose dual attention networks (DAN) for visual reference resolution in VisDial. |
| Outcome: | The proposed model outperforms the previous state-of-the-art model on VisDial datasets. |