Web: http://arxiv.org/abs/2209.08626

Sept. 20, 2022, 1:14 a.m. | Linzi Xing, Patrick Huber, Giuseppe Carenini

cs.CL updates on arXiv.org arxiv.org

Recent neural supervised topic segmentation models achieve distinguished
superior effectiveness over unsupervised methods, with the availability of
large-scale training corpora sampled from Wikipedia. These models may, however,
suffer from limited robustness and transferability caused by exploiting simple
linguistic cues for prediction, but overlooking more important inter-sentential
topical consistency. To address this issue, we present a discourse-aware neural
topic segmentation model with the injection of above-sentence discourse
dependency structures to encourage the model make topic boundary prediction
based more on the …

arxiv dependencies segmentation

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