activity
20182023
most citedMASS: Masked Sequence to Sequence Pre-training for Language Generation

578 citations · 2.9k across the 69 of their papers we have counts for

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Showing 2019 · cs.CLShow all

10 papers · 2 filters

cs.CL2019★ 8 cited

A Study of Multilingual Neural Machine Translation

Xu Tan, Yichong Leng, Jiale Chen +3

Multilingual neural machine translation (NMT) has recently been investigated from different aspects (e.g., pivot translation, zero-shot translation, fine-tuning, or training from s…

cs.CL2019

Microsoft Research Asia's Systems for WMT19

Yingce Xia, Xu Tan, Fei Tian +11

We Microsoft Research Asia made submissions to 11 language directions in the WMT19 news translation tasks. We won the first place for 8 of the 11 directions and the second place fo…

cs.CL2019★ 12 cited

ESPnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit

Tomoki Hayashi, Ryuichi Yamamoto, Katsuki Inoue +6

This paper introduces a new end-to-end text-to-speech (E2E-TTS) toolkit named ESPnet-TTS, which is an extension of the open-source speech processing toolkit ESPnet. The toolkit sup…

cs.CL2019★ 3 cited

Efficient Bidirectional Neural Machine Translation

Xu Tan, Yingce Xia, Lijun Wu +1

The encoder-decoder based neural machine translation usually generates a target sequence token by token from left to right. Due to error propagation, the tokens in the right side o…

cs.CL2019★ 12 cited

Multilingual Neural Machine Translation with Language Clustering

Xu Tan, Jiale Chen, Di He +3

Multilingual neural machine translation (NMT), which translates multiple languages using a single model, is of great practical importance due to its advantages in simplifying the t…

cs.CL2019★ 8 cited

Hard but Robust, Easy but Sensitive: How Encoder and Decoder Perform in Neural Machine Translation

Tianyu He, Xu Tan, Tao Qin

Neural machine translation (NMT) typically adopts the encoder-decoder framework. A good understanding of the characteristics and functionalities of the encoder and decoder can help…

cs.CL2019★ 8 cited

Language Graph Distillation for Low-Resource Machine Translation

Tianyu He, Jiale Chen, Xu Tan +1

Neural machine translation on low-resource language is challenging due to the lack of bilingual sentence pairs. Previous works usually solve the low-resource translation problem wi…

cs.CL2019★ 3 cited

Unsupervised Pivot Translation for Distant Languages

Yichong Leng, Xu Tan, Tao Qin +2

Unsupervised neural machine translation (NMT) has attracted a lot of attention recently. While state-of-the-art methods for unsupervised translation usually perform well between si…

cs.CL2019★ 578 cited

MASS: Masked Sequence to Sequence Pre-training for Language Generation

Kaitao Song, Xu Tan, Tao Qin +2

Pre-training and fine-tuning, e.g., BERT, have achieved great success in language understanding by transferring knowledge from rich-resource pre-training task to the low/zero-resou…

cs.CL2019★ 128 cited

Multilingual Neural Machine Translation with Knowledge Distillation

Xu Tan, Yi Ren, Di He +3

Multilingual machine translation, which translates multiple languages with a single model, has attracted much attention due to its efficiency of offline training and online serving…