51 citations · 84 across the 9 of their papers we have counts for
12 papers
Document-Level Relation Extraction with Sentences Importance Estimation and Focusing
Wang Xu, Kehai Chen, Lili Mou +1
Document-level relation extraction (DocRE) aims to determine the relation between two entities from a document of multiple sentences. Recent studies typically represent the entire…
Text Compression-aided Transformer Encoding
Zuchao Li, Zhuosheng Zhang, Hai Zhao +4
Text encoding is one of the most important steps in Natural Language Processing (NLP). It has been done well by the self-attention mechanism in the current state-of-the-art Transfo…
Document-Level Relation Extraction with Reconstruction
Wang Xu, Kehai Chen, Tiejun Zhao
In document-level relation extraction (DocRE), graph structure is generally used to encode relation information in the input document to classify the relation category between each…
SJTU-NICT's Supervised and Unsupervised Neural Machine Translation Systems for the WMT20 News Translation Task
Zuchao Li, Hai Zhao, Rui Wang +3
In this paper, we introduced our joint team SJTU-NICT 's participation in the WMT 2020 machine translation shared task. In this shared task, we participated in four translation dir…
Knowledge Distillation for Multilingual Unsupervised Neural Machine Translation
Haipeng Sun, Rui Wang, Kehai Chen +3
Unsupervised neural machine translation (UNMT) has recently achieved remarkable results for several language pairs. However, it can only translate between a single language pair an…
Explicit Reordering for Neural Machine Translation
Kehai Chen, Rui Wang, Masao Utiyama +1
In Transformer-based neural machine translation (NMT), the positional encoding mechanism helps the self-attention networks to learn the source representation with order dependency,…