Discourse Parsing with Attention-based Hierarchical Neural Networks
Published in EMNLP 2016, 2016
Recommended citation: Qi Li, Tianshi Li, and Baobao Chang. "Discourse Parsing with Attention-based Hierarchical Neural Networks." EMNLP. 2016. https://aclanthology.org/D16-1035.pdf
RST-style document-level discourse parsing remains a difficult task and efficient deep learning models on this task have rarely been presented. In this paper, we propose an attention-based hierarchical neural network model for discourse parsing. We also incorporate tensor-based transformation function to model complicated feature interactions. Experimental results show that our approach obtains comparable performance to the contemporary state-of-the-art systems with little manual feature engineering.
Recommended citation: Qi Li, Tianshi Li, and Baobao Chang. “Discourse Parsing with Attention-based Hierarchical Neural Networks.” EMNLP. 2016.