Papers by Yu-Seop Kim
Lightweight Text Classifier using Sinusoidal Positional Encoding (2020.aacl-main)
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| Challenge: | Large and complex models require many parameters and time to solve various problems in natural language processing. |
| Approach: | They propose to use the sinusoidal positional encoding (SPE) to construct a convolutional neural network using the SPE in text classification. |
| Outcome: | The proposed model reduces parameter size and training time while maintaining similar performance to the current model on multiple benchmark datasets. |