Search Results for author:
Found 2 papers, 1 papers with code
Enhancing Low-resource Fine-grained Named Entity Recognition by Leveraging Coarse-grained Datasets
Although $K$-shot learning techniques can be applied, their performance tends to saturate when the number of annotations exceeds several tens of labels.
Data Augmentation for Neural Machine Translation using Generative Language Model
Data augmentation is a technique that enhances the performance of data-hungry models by generating synthetic data instead of collecting new ones.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
