activity
20202025
most citedLanguage Is Not All You Need: Aligning Perception with Language Models

164 citations · 550 across the 15 of their papers we have counts for

collaborators
Showing 2021Show all

6 papers · 1 filter

cs.CL2021★ 15 cited

Multilingual Machine Translation Systems from Microsoft for WMT21 Shared Task

Jian Yang, Shuming Ma, Haoyang Huang +8

This report describes Microsoft's machine translation systems for the WMT21 shared task on large-scale multilingual machine translation. We participated in all three evaluation tra…

cs.CL2021

Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training

Bo Zheng, Li Dong, Shaohan Huang +5

Compared to monolingual models, cross-lingual models usually require a more expressive vocabulary to represent all languages adequately. We find that many languages are under-repre…

cs.CL2021★ 5 cited

Consistency Regularization for Cross-Lingual Fine-Tuning

Bo Zheng, Li Dong, Shaohan Huang +7

Fine-tuning pre-trained cross-lingual language models can transfer task-specific supervision from one language to the others. In this work, we propose to improve cross-lingual fine…

cs.CL2021★ 24 cited

XLM-E: Cross-lingual Language Model Pre-training via ELECTRA

Zewen Chi, Shaohan Huang, Li Dong +8

In this paper, we introduce ELECTRA-style tasks to cross-lingual language model pre-training. Specifically, we present two pre-training tasks, namely multilingual replaced token de…

cs.CL2021★ 51 cited

DeltaLM: Encoder-Decoder Pre-training for Language Generation and Translation by Augmenting Pretrained Multilingual Encoders

Shuming Ma, Li Dong, Shaohan Huang +6

While pretrained encoders have achieved success in various natural language understanding (NLU) tasks, there is a gap between these pretrained encoders and natural language generat…

cs.CL2021★ 1 cited

MT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs

Zewen Chi, Li Dong, Shuming Ma +3

Multilingual T5 (mT5) pretrains a sequence-to-sequence model on massive monolingual texts, which has shown promising results on many cross-lingual tasks. In this paper, we improve…