28 citations · 63 across the 5 of their papers we have counts for
5 papers · 1 filter
Lightweight, Dynamic Graph Convolutional Networks for AMR-to-Text Generation
Yan Zhang, Zhijiang Guo, Zhiyang Teng +4
AMR-to-text generation is used to transduce Abstract Meaning Representation structures (AMR) into text. A key challenge in this task is to efficiently learn effective graph represe…
Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders
Jue Wang, Wei Lu
Named entity recognition and relation extraction are two important fundamental problems. Joint learning algorithms have been proposed to solve both tasks simultaneously, and many o…
Position-Aware Tagging for Aspect Sentiment Triplet Extraction
Lu Xu, Hao Li, Wei Lu +1
Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting the triplets of target entities, their associated sentiment, and opinion spans explaining the reason for the se…
Reasoning with Latent Structure Refinement for Document-Level Relation Extraction
Guoshun Nan, Zhijiang Guo, Ivan Sekulić +1
Document-level relation extraction requires integrating information within and across multiple sentences of a document and capturing complex interactions between inter-sentence ent…
Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model
Guoxiu He, Zhe Gao, Zhuoren Jiang +4
The nonliteral interpretation of a text is hard to be understood by machine models due to its high context-sensitivity and heavy usage of figurative language. In this study, inspir…