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20192022
most citedLearning Deep Transformer Models for Machine Translation

97 citations · 114 across the 9 of their papers we have counts for

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10 papers · 1 filter

cs.CL20222 cited

ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation

Bei Li, Quan Du, Tao Zhou +7

Residual networks are an Euler discretization of solutions to Ordinary Differential Equations (ODE). This paper explores a deeper relationship between Transformer and numerical ODE…

cs.CL2022

On Vision Features in Multimodal Machine Translation

Bei Li, Chuanhao Lv, Zefan Zhou +4

Previous work on multimodal machine translation (MMT) has focused on the way of incorporating vision features into translation but little attention is on the quality of vision mode…

cs.CL20211 cited

The NiuTrans Machine Translation Systems for WMT21

Shuhan Zhou, Tao Zhou, Binghao Wei +15

This paper describes NiuTrans neural machine translation systems of the WMT 2021 news translation tasks. We made submissions to 9 language directions, including English$\leftrighta…

cs.CL2021

The NiuTrans System for WNGT 2020 Efficiency Task

Chi Hu, Bei Li, Ye Lin +5

This paper describes the submissions of the NiuTrans Team to the WNGT 2020 Efficiency Shared Task. We focus on the efficient implementation of deep Transformer models \cite{wang-et…

cs.CL2021

The NiuTrans System for the WMT21 Efficiency Task

Chenglong Wang, Chi Hu, Yongyu Mu +8

This paper describes the NiuTrans system for the WMT21 translation efficiency task (http://statmt.org/wmt21/efficiency-task.html). Following last year's work, we explore various te…

cs.CL202111 cited

ODE Transformer: An Ordinary Differential Equation-Inspired Model for Neural Machine Translation

Bei Li, Quan Du, Tao Zhou +4

It has been found that residual networks are an Euler discretization of solutions to Ordinary Differential Equations (ODEs). In this paper, we explore a deeper relationship between…