In this work, I propose a fully data-driven approach to abstractive sentence summarization. My method utilizes a local attention-based model that generates each word of the summary conditioned on the input sentence. While the model is structurally simple, it can easily be trained end-to-end and scales to a large amount of training data. The model shows significant performance gains on the DUC-2004 shared task compared with several strong baselines.
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In this work, I propose a fully data-driven approach to abstractive sentence summarization. My method utilizes a local attention-based model that generates each word of the summary conditioned on the input sentence. While the model is structurally simple, it can easily be trained end-to-end and scales to a large amount of training data. The mode…
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codeninja404/abstractiveSentenceSummarization
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In this work, I propose a fully data-driven approach to abstractive sentence summarization. My method utilizes a local attention-based model that generates each word of the summary conditioned on the input sentence. While the model is structurally simple, it can easily be trained end-to-end and scales to a large amount of training data. The mode…
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