Papers with Unsupervised pre-training of large neural models

1 papers
Leveraging Pre-trained Checkpoints for Sequence Generation Tasks (2020.tacl-1)

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Challenge: Unsupervised pre-training of large neural models has revolutionized Natural Language Processing.
Approach: They propose to use pre-trained checkpoints for Sequence Generation to initialize a Transformer-based sequence-to-sequence model that is compatible with these checkpoint.
Outcome: The proposed model is compatible with pre-trained BERT, GPT-2, and RoBERTa checkpoints and achieves state-of-the-art results on Machine Translation, Text Summarization, Sentence Splitting, and Sentance Fusion.

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