Papers by Jemin Park

1 papers
Align-to-Distill: Trainable Attention Alignment for Knowledge Distillation in Neural Machine Translation (2024.lrec-main)

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Challenge: Existing knowledge distillation approaches to NMT often rely on heuristics when deciding which teacher layers to distill from.
Approach: They propose an approach to align student attention heads with their teacher counterparts by heuristics to solve a feature mapping problem.
Outcome: The proposed strategy shows gains of +3.61 and +0.63 BLEU points for WMT-2022 DeDsb and WMT-2014 EnDe compared to baselines.

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