Open access
Jul 2026
Improving low-resource neural machine translation by semantic distance augmentation
A semantic distance augmentation (SDA) method that integrates syntactic information from constituency parse trees into the NMT encoder to optimize self-attention and achieves statistically significant improvements in translation quality over the strong baseline, without requiring additional training data or increasing model complexity.
Fuxue Li, Hong Yan, Chuncheng Chi et al.
· PeerJ Computer Science · 0 citations