11 citations · 58 across the 20 of their papers we have counts for
29 papers
Efficient Cluster-Based k-Nearest-Neighbor Machine Translation
Dexin Wang, Kai Fan, Boxing Chen +1
k-Nearest-Neighbor Machine Translation (kNN-MT) has been recently proposed as a non-parametric solution for domain adaptation in neural machine translation (NMT). It aims to allevi…
Secoco: Self-Correcting Encoding for Neural Machine Translation
Tao Wang, Chengqi Zhao, Mingxuan Wang +3
This paper presents Self-correcting Encoding (Secoco), a framework that effectively deals with input noise for robust neural machine translation by introducing self-correcting pred…
Autocorrect in the Process of Translation -- Multi-task Learning Improves Dialogue Machine Translation
Tao Wang, Chengqi Zhao, Mingxuan Wang +2
Automatic translation of dialogue texts is a much needed demand in many real life scenarios. However, the currently existing neural machine translation delivers unsatisfying result…
Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention Learning
Jinsong Su, Jialong Tang, Hui Jiang +6
In aspect-based sentiment analysis (ABSA), many neural models are equipped with an attention mechanism to quantify the contribution of each context word to sentiment prediction. Ho…
Integrating Pre-trained Model into Rule-based Dialogue Management
Jun Quan, Meng Yang, Qiang Gan +9
Rule-based dialogue management is still the most popular solution for industrial task-oriented dialogue systems for their interpretablility. However, it is hard for developers to m…
Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding
Dexin Wang, Deyi Xiong
Visual context provides grounding information for multimodal machine translation (MMT). However, previous MMT models and probing studies on visual features suggest that visual info…