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20192026
most citedLanguage Is Not All You Need: Aligning Perception with Language Models

164 citations · 315 across the 29 of their papers we have counts for

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Showing 2021Show all

7 papers · 1 filter

cs.CL2021

Unifying Cross-lingual Summarization and Machine Translation with Compression Rate

Yu Bai, Heyan Huang, Kai Fan +5

Cross-Lingual Summarization (CLS) is a task that extracts important information from a source document and summarizes it into a summary in another language. It is a challenging tas…

cs.CL2021★ 1 cited

Cross-Lingual Language Model Meta-Pretraining

Zewen Chi, Heyan Huang, Luyang Liu +2

The success of pretrained cross-lingual language models relies on two essential abilities, i.e., generalization ability for learning downstream tasks in a source language, and cros…

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

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★ 1 cited

Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word Alignment

Zewen Chi, Li Dong, Bo Zheng +4

The cross-lingual language models are typically pretrained with masked language modeling on multilingual text or parallel sentences. In this paper, we introduce denoising word alig…

cs.CL2021

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…