PDAMeta: Meta-Learning Framework with Progressive Data Augmentation for Few-Shot Text Classification
Xurui Li, Kaisong Song, Tianqianjin Lin, Yangyang Kang, Fubang Zhao, Changlong Sun, Xiaozhong Liu
Abstract
Recently, we have witnessed the breakthroughs of meta-learning for few-shot learning scenario. Data augmentation is essential for meta-learning, particularly in situations where data is extremely scarce. However, existing text data augmentation methods can not ensure the diversity and quality of the generated data, which leads to sub-optimal performance. Inspired by the recent success of large language models (LLMs) which demonstrate improved language comprehension abilities, we propose a Meta-learning framework with Progressive Data Augmentation (PDAMeta) for few-shot text classification, which contains a two-stage data augmentation strategy. First, the prompt-based data augmentation enriches the diversity of the training instances from a global perspective. Second, the attention-based data augmentation further improves the data quality from a local perspective. Last, we propose a dual-stream contrastive meta-learning strategy to learn discriminative text representations from both original and augmented instances. Extensive experiments conducted on four public few-shot text classification datasets show that PDAMeta significantly outperforms several state-of-the-art models and shows better robustness.- Anthology ID:
- 2024.lrec-main.1109
- Volume:
- Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
- Venues:
- LREC | COLING
- SIG:
- Publisher:
- ELRA and ICCL
- Note:
- Pages:
- 12668–12678
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.lrec-main.1109/
- DOI:
- Cite (ACL):
- Xurui Li, Kaisong Song, Tianqianjin Lin, Yangyang Kang, Fubang Zhao, Changlong Sun, and Xiaozhong Liu. 2024. PDAMeta: Meta-Learning Framework with Progressive Data Augmentation for Few-Shot Text Classification. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 12668–12678, Torino, Italia. ELRA and ICCL.
- Cite (Informal):
- PDAMeta: Meta-Learning Framework with Progressive Data Augmentation for Few-Shot Text Classification (Li et al., LREC-COLING 2024)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.lrec-main.1109.pdf