Yinhan Liu | DeepAI

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∙ 04/15/2021

Hierarchical Learning for Generation with Long Source Sequences

One of the challenges for current sequence to sequence (seq2seq) models ...

0 Tobias Rohde, et al. ∙

∙ 04/28/2020

Recipes for building an open-domain chatbot

Building open-domain chatbots is a challenging area for machine learning...

6 Stephen Roller, et al. ∙

∙ 01/22/2020

Multilingual Denoising Pre-training for Neural Machine Translation

This paper demonstrates that multilingual denoising pre-training produce...

0 Yinhan Liu, et al. ∙

∙ 10/29/2019

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

We present BART, a denoising autoencoder for pretraining sequence-to-seq...

35 Mike Lewis, et al. ∙

∙ 07/26/2019

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Language model pretraining has led to significant performance gains but ...

0 Yinhan Liu, et al. ∙

∙ 07/24/2019

SpanBERT: Improving Pre-training by Representing and Predicting Spans

We present SpanBERT, a pre-training method that is designed to better re...

0 Mandar Joshi, et al. ∙

∙ 04/19/2019

Constant-Time Machine Translation with Conditional Masked Language Models

Most machine translation systems generate text autoregressively, by sequ...

6 Marjan Ghazvininejad, et al. ∙

∙ 03/19/2019

Cloze-driven Pretraining of Self-attention Networks

We present a new approach for pretraining a bi-directional transformer m...

0 Alexei Baevski, et al. ∙

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