activity
20182024
most citedTorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery

32 citations · 32 across the 6 of their papers we have counts for

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Showing cs.CLShow all

7 papers · 1 filter

cs.CL2022

Data-Driven Adaptive Simultaneous Machine Translation

Guangxu Xun, Mingbo Ma, Yuchen Bian +7

In simultaneous translation (SimulMT), the most widely used strategy is the wait-k policy thanks to its simplicity and effectiveness in balancing translation quality and latency. H…

cs.CL2021

Direct Simultaneous Speech-to-Text Translation Assisted by Synchronized Streaming ASR

Junkun Chen, Mingbo Ma, Renjie Zheng +1

Simultaneous speech-to-text translation is widely useful in many scenarios. The conventional cascaded approach uses a pipeline of streaming ASR followed by simultaneous MT, but suf…

cs.CL2021

Fused Acoustic and Text Encoding for Multimodal Bilingual Pretraining and Speech Translation

Renjie Zheng, Junkun Chen, Mingbo Ma +1

Recently, representation learning for text and speech has successfully improved many language related tasks. However, all existing methods suffer from two limitations: (a) they onl…

cs.CL2020

MAM: Masked Acoustic Modeling for End-to-End Speech-to-Text Translation

Junkun Chen, Mingbo Ma, Renjie Zheng +1

End-to-end Speech-to-text Translation (E2E-ST), which directly translates source language speech to target language text, is widely useful in practice, but traditional cascaded app…

cs.CL2020

Improving Simultaneous Translation by Incorporating Pseudo-References with Fewer Reorderings

Junkun Chen, Renjie Zheng, Atsuhito Kita +2

Simultaneous translation is vastly different from full-sentence translation, in the sense that it starts translation before the source sentence ends, with only a few words delay. H…

cs.CL2019

DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks

Lin Zehui, Pengfei Liu, Luyao Huang +3

Variants dropout methods have been designed for the fully-connected layer, convolutional layer and recurrent layer in neural networks, and shown to be effective to avoid overfittin…