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Generation-Distillation for Efficient Natural Language Understanding in Low-Data Settings
Recent research points to knowledge distillation as a potential solution, showing that when training data for a given task is abundant, it is possible to distill a large (teacher) LM into a small task-specific (student) network with minimal loss of performance.
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