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

11 citations · 23 across the 12 of their papers we have counts for

collaborators

15 papers

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

RankNAS: Efficient Neural Architecture Search by Pairwise Ranking

Chi Hu, Chenglong Wang, Xiangnan Ma +5

This paper addresses the efficiency challenge of Neural Architecture Search (NAS) by formulating the task as a ranking problem. Previous methods require numerous training examples…

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.LG2021

Bag of Tricks for Optimizing Transformer Efficiency

Ye Lin, Yanyang Li, Tong Xiao +1

Improving Transformer efficiency has become increasingly attractive recently. A wide range of methods has been proposed, e.g., pruning, quantization, new architectures and etc. But…

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…

cs.CL20214 cited

Non-Autoregressive Translation by Learning Target Categorical Codes

Yu Bao, Shujian Huang, Tong Xiao +3

Non-autoregressive Transformer is a promising text generation model. However, current non-autoregressive models still fall behind their autoregressive counterparts in translation q…