A Genre-Aware Attention Model to Improve the Likability Prediction of Books (D18-1)
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| Challenge: | Existing methods for likability prediction are time-consuming and too rigid. |
| Approach: | They propose a novel neural architecture that incorporates genre supervision to assign weights to individual feature types based on the characteristics of each book. |
| Outcome: | The proposed method outperforms state-of-the-art methods and achieves competitive results. |
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A Hierarchical Neural Attention-based Text Classifier (D18-1)
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| Challenge: | Neural network models for many NLP tasks have grown increasingly complex in recent years . authors of recent papers question the necessity of such architectures and find them quite effective . |
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Estimating Confidence of Predictions of Individual Classifiers and TheirEnsembles for the Genre Classification Task (2022.lrec-1)
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| Challenge: | Genre identification is a kind of non-topic text classification. genre is defined as a functional space. |
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