Understanding Knowledge Distillation in Neural Sequence Generation
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Understanding Knowledge Distillation in Neural Sequence Generation
Sequence-level knowledge distillation (KD) — learning a student model with targets decoded from a pre-trained teacher model — has been widely used in sequence generation applications (e.g. model compression, non-autoregressive translation (NAT), low-resource translation, etc). However, the underlying reasons behind this success have, as of ...
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