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Text Embedding Augmentation Based on Retraining With Pseudo-Labeled Adversarial Embedding

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Pre-trained language models (LMs) have been shown to achieve outstanding performance in various natural language processing tasks; however. these models have a significantly large number of parameters to handle large-scale text corpora during the pre-training process. and thus. they entail the risk of overfitting when fine-tuning for small task-oriented datasets is conducted. https://www.thebanyantreers.shop/product-category/canvas/
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