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cs.CL2019
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
Xiaozhi Wang, Tianyu Gao, Zhaocheng Zhu +4
Pre-trained language representation models (PLMs) cannot well capture factual knowledge from text. In contrast, knowledge embedding (KE) methods can effectively represent the relat…
cs.CL2018
Contextualized Non-local Neural Networks for Sequence Learning
Pengfei Liu, Shuaichen Chang, Xuanjing Huang +2
Recently, a large number of neural mechanisms and models have been proposed for sequence learning, of which self-attention, as exemplified by the Transformer model, and graph neura…