  We propose the first multi-task learning model for joint Vietnamese word
segmentation, part-of-speech (POS) tagging and dependency parsing. In
particular, our model extends the BIST graph-based dependency parser
(Kiperwasser and Goldberg, 2016) with BiLSTM-CRF-based neural layers (Huang et
al., 2015) for word segmentation and POS tagging. On Vietnamese benchmark
datasets, experimental results show that our joint model obtains
state-of-the-art or competitive performances.
