Papers with neural architecture search inspired approach

1 papers
Learning Language-Specific Layers for Multilingual Machine Translation (2023.acl-long)

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Challenge: Multilingual Machine Translation (MNMT) is a promising new approach to improve translation quality between non-English languages.
Approach: They propose a language-specific transformer layer to increase model capacity while keeping computation and parameters constant.
Outcome: The proposed approach improves translation quality by 1.3 chrF (1.5 spBLEU) over not using LSLs on a separate decoder architecture.

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