activity
20162023
most citedA Survey of Domain Adaptation for Neural Machine Translation

195 citations · 493 across the 31 of their papers we have counts for

collaborators
Showing 2019Show all

8 papers · 1 filter

cs.CL2019★ 3 cited

Explicit Sentence Compression for Neural Machine Translation

Zuchao Li, Rui Wang, Kehai Chen +4

State-of-the-art Transformer-based neural machine translation (NMT) systems still follow a standard encoder-decoder framework, in which source sentence representation can be well d…

cs.CL2019★ 2 cited

Probing Contextualized Sentence Representations with Visual Awareness

Zhuosheng Zhang, Rui Wang, Kehai Chen +3

We present a universal framework to model contextualized sentence representations with visual awareness that is motivated to overcome the shortcomings of the multimodal parallel da…

cs.CL2019★ 1 cited

Dependency and Span, Cross-Style Semantic Role Labeling on PropBank and NomBank

Zuchao Li, Hai Zhao, Junru Zhou +2

The latest developments in neural semantic role labeling (SRL) have shown great performance improvements with both the dependency and span formalisms/styles. Although the two style…

cs.CL2019

Document-level Neural Machine Translation with Associated Memory Network

Shu Jiang, Rui Wang, Zuchao Li +5

Standard neural machine translation (NMT) is on the assumption that the document-level context is independent. Most existing document-level NMT approaches are satisfied with a smat…

cs.CL2019

Regularized Context Gates on Transformer for Machine Translation

Xintong Li, Lemao Liu, Rui Wang +2

Context gates are effective to control the contributions from the source and target contexts in the recurrent neural network (RNN) based neural machine translation (NMT). However,…

cs.CL2019★ 2 cited

Controllable Dual Skew Divergence Loss for Neural Machine Translation

Zuchao Li, Hai Zhao, Yingting Wu +2

In sequence prediction tasks like neural machine translation, training with cross-entropy loss often leads to models that overgeneralize and plunge into local optima. In this paper…

cs.CL2019★ 25 cited

SG-Net: Syntax-Guided Machine Reading Comprehension

Zhuosheng Zhang, Yuwei Wu, Junru Zhou +3

For machine reading comprehension, the capacity of effectively modeling the linguistic knowledge from the detail-riddled and lengthy passages and getting ride of the noises is esse…

cs.CL2019★ 9 cited

Lattice-Based Transformer Encoder for Neural Machine Translation

Fengshun Xiao, Jiangtong Li, Hai Zhao +2

Neural machine translation (NMT) takes deterministic sequences for source representations. However, either word-level or subword-level segmentations have multiple choices to split…