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20182020
most citedBroadband Analog Aggregation for Low-Latency Federated Edge Learning (Extended Version)

38 citations · 54 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CL20201 cited

Unsupervised Domain Adaptation of a Pretrained Cross-Lingual Language Model

Juntao Li, Ruidan He, Hai Ye +3

Recent research indicates that pretraining cross-lingual language models on large-scale unlabeled texts yields significant performance improvements over various cross-lingual and l…

cs.CL2020

On the Sparsity of Neural Machine Translation Models

Yong Wang, Longyue Wang, Victor O. K. Li +1

Modern neural machine translation (NMT) models employ a large number of parameters, which leads to serious over-parameterization and typically causes the underutilization of comput…

cs.CL20192 cited

Go From the General to the Particular: Multi-Domain Translation with Domain Transformation Networks

Yong Wang, Longyue Wang, Shuming Shi +2

The key challenge of multi-domain translation lies in simultaneously encoding both the general knowledge shared across domains and the particular knowledge distinctive to each doma…

cs.CL201913 cited

Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations

Jiatao Gu, Yong Wang, Kyunghyun Cho +1

Zero-shot translation, translating between language pairs on which a Neural Machine Translation (NMT) system has never been trained, is an emergent property when training the syste…

cs.CL2018

Meta-Learning for Low-Resource Neural Machine Translation

Jiatao Gu, Yong Wang, Yun Chen +2

In this paper, we propose to extend the recently introduced model-agnostic meta-learning algorithm (MAML) for low-resource neural machine translation (NMT). We frame low-resource t…