1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2024
Align-to-Distill: Trainable Attention Alignment for Knowledge Distillation in Neural Machine Translation
Heegon Jin, Seonil Son, Jemin Park +3
The advent of scalable deep models and large datasets has improved the performance of Neural Machine Translation. Knowledge Distillation (KD) enhances efficiency by transferring kn…
cs.CL2021★ 1 cited
May the Force Be with Your Copy Mechanism: Enhanced Supervised-Copy Method for Natural Language Generation
Sanghyuk Choi, Jeong-in Hwang, Hyungjong Noh +1
Recent neural sequence-to-sequence models with a copy mechanism have achieved remarkable progress in various text generation tasks. These models addressed out-of-vocabulary problem…