BERT as a Teacher: Contextual Embeddings for Sequence-Level Reward

Schmidt Florian
Schmidt Florian
Cited by: 0|Views7

Abstract:

Measuring the quality of a generated sequence against a set of references is a central problem in many learning frameworks, be it to compute a score, to assign a reward, or to perform discrimination. Despite great advances in model architectures, metrics that scale independently of the number of references are still based on n-gram esti...More

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