Although the in-word negative sampling method proposed above is expected to prevent our model from incorrectly splitting multi-character words, we still want our model to pay more attention to the segmentation of such words.
• On four datasets in different special domains, our model improves the word F-measure by more than 3.0%, compared with the state-ofthe-art baseline segmenter.