Papers with data insufficiency

1 papers
Toward Fast and Accurate Neural Discourse Segmentation (D18-1)

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Challenge: Existing discourse segmenters rely on complicated hand-crafted features and are not practical in actual use.
Approach: They propose an end-to-end neural segmenter based on BiLSTM-CRF framework that can segment texts fast and accurately using a large corpus.
Outcome: The proposed model is significantly faster than previous methods while achieving state-of-the-art performance on the RST-DT corpus.

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