Deep reinforced model for abstractive summarization
Abstract:
A system for text summarization includes an encoder for encoding input tokens of a document and a decoder for emitting summary tokens which summarize the document based on the encoded input tokens. At each iteration the decoder generates attention scores between a current hidden state of the decoder and previous hidden states of the decoder, generates a current decoder context from the attention scores and the previous hidden states of the decoder, and selects a next summary token based on the current decoder context. The selection of the next summary token prevents emission of repeated summary phrases in a summary of the document.
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