MLE-guided parameter search for task loss minimization in neural sequence modeling

4 Jun 2020 Sean Welleck Kyunghyun Cho

Neural autoregressive sequence models are used to generate sequences in a variety of natural language processing (NLP) tasks, where they are evaluated according to sequence-level task losses. These models are typically trained with maximum likelihood estimation, which ignores the task loss, yet empirically performs well as a surrogate objective... (read more)

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