Automatic Rule Induction for Efficient Semi-Supervised Learning
Reid Pryzant, Ziyi Yang, Yichong Xu, Chenguang Zhu, Michael Zeng
Abstract
Semi-supervised learning has shown promise in allowing NLP models to generalize from small amounts of labeled data. Meanwhile, pretrained transformer models act as black-box correlation engines that are difficult to explain and sometimes behave unreliably. In this paper, we propose tackling both of these challenges via Automatic Rule Induction (ARI), a simple and general-purpose framework for the automatic discovery and integration of symbolic rules into pretrained transformer models. First, we extract weak symbolic rules from low-capacity machine learning models trained on small amounts of labeled data. Next, we use an attention mechanism to integrate these rules into high-capacity pretrained transformer models. Last, the rule-augmented system becomes part of a self-training framework to boost supervision signal on unlabeled data. These steps can be layered beneath a variety of existing weak supervision and semi-supervised NLP algorithms in order to improve performance and interpretability. Experiments across nine sequence classification and relation extraction tasks suggest that ARI can improve state-of-the-art methods with no manual effort and minimal computational overhead.- Anthology ID:
- 2022.findings-emnlp.3
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2022
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates
- Editors:
- Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 28–44
- Language:
- URL:
- https://aclanthology.org/2022.findings-emnlp.3
- DOI:
- 10.18653/v1/2022.findings-emnlp.3
- Cite (ACL):
- Reid Pryzant, Ziyi Yang, Yichong Xu, Chenguang Zhu, and Michael Zeng. 2022. Automatic Rule Induction for Efficient Semi-Supervised Learning. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 28–44, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
- Cite (Informal):
- Automatic Rule Induction for Efficient Semi-Supervised Learning (Pryzant et al., Findings 2022)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/2022.findings-emnlp.3.pdf