To manage this issue we apply kernel smoothing over the language model to adapt it from the full vocab V down to the candidate word list C. Our smoothing process focuses on the output embeddings from the pretrained language model.
in abstractive summarization, we use K = 6 in the candidate list and use the fixed embeddings at the bottom layer of ELMo language model for similarity.