Papers with encoder and decoder layers

2 papers
Towards Making the Most of Cross-Lingual Transfer for Zero-Shot Neural Machine Translation (2022.acl-long)

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Challenge: Existing unsupervised neural machine translation systems can degrade when labeled data is limited.
Approach: They propose a multilingual pretraining and multilingual fine-tuning for facilitating cross-lingual transfer in zero-shot translation using a parallel dataset.
Outcome: The proposed model outperforms state-of-the-art models on many-to-English translation by over 7.2 and 5.0 BLEU.
Soft Layer-Specific Multi-Task Summarization with Entailment and Question Generation (P18-1)

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Challenge: Recent advances on abstractive summarization have allowed substantial improvements in the quality of the model, but there is still scope for improvement.
Approach: They propose novel multi-task architectures with high-level layer-specific sharing across multiple encoder and decoder layers of the three tasks and soft-sharing mechanisms.
Outcome: The proposed model improves on the CNN/DailyMail and Gigaword datasets and on the DUC-2002 transfer setup.

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