Papers with shallow decoders

1 papers
Multilingual Neural Machine Translation with Deep Encoder and Multiple Shallow Decoders (2021.eacl-main)

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Challenge: Recent work in multilingual translation has improved translation quality surpassing bilingual baselines using deep transformer models with increased capacity.
Approach: They propose a deep encoder with multiple shallow decoders to reduce inference latency while maintaining translation quality.
Outcome: The proposed model achieves 1.8x speedup on average compared to a standard transformer model with no drop in translation quality.

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