This paper focuses on the Data Augmentation for low-resource Natural Language Understanding (NLU) tasks. We propose Prompt-based Data Augmentation model (PromDA)�...

Feb 25, 2022 � This paper focuses on the Data Augmentation for low-resource Natural Language Understanding (NLU) tasks. We propose Prompt-based D}ata Augmentation model (�...

This repository is the official implementation of PromDA: Prompt-based Data Augmentation for Low-Resource NLU Tasks.

Experiments on four benchmarks show that synthetic data produced by PromDA successfully boost up the performance of NLU models which consistently outperform�...

Jun 13, 2024 � This paper focuses on the Data Augmentation for low-resource Natural Language Understanding (NLU) tasks. We propose Prompt-based D}ata�...

We propose Prompt-based Data Augmentation model (PromDA) which only trains small-scale Soft Prompt (i.e., a set of trainable vectors) in the frozen Pre-trained�...

Apr 4, 2022 � Experiments on four benchmarks show the effectiveness of our proposed PromDA method. In the future, we plan to expand. PromDA to other NLP tasks�...

Data augmentation has been widely used in low-resource. NER tasks to tackle the problem of data sparsity. How- ever, previous data augmentation methods have�...

Jun 6, 2024 � We present ABEX, a novel and effective generative data augmentation methodology for low-resource Natural Language Understanding (NLU) tasks.

May 22, 2023 � Data Augmentation을 위해 고안된 Soft Prompt를 활용한 최초의 PLM � PromDA로 만든 synthetic data로 정답이 없는 (unlabeled) in-domain data 보완 가능.