资源论文swim a simple word interaction model for implicit discourse relation recognition

swim a simple word interaction model for implicit discourse relation recognition

2019-10-31 | |  36 |   29 |   0
Abstract words across arguments and proper argument representation are both crucial issues in implicit discourse relation recognition. The current state-ofthe-art represents arguments as distributional vectors that are computed via bi-directional Long Short-Term Memory networks (BiLSTMs), known to have significant model complexity. In contrast, we demonstrate that word-weighted averaging can encode argument representation which can be incorporated with word pair information efficiently. By saving an order of magnitude in parameters and eschewing the recurrent structure, our proposed model achieves equivalent performance, but trains seven times faster.

上一篇:contextcare incorporating contextual information networks to representation learning on medical forum data

下一篇:projective low rank subspace clustering via learning deep encoder

用户评价
全部评价

热门资源

  • Learning to Predi...

    Much of model-based reinforcement learning invo...

  • Stratified Strate...

    In this paper we introduce Stratified Strategy ...

  • The Variational S...

    Unlike traditional images which do not offer in...

  • Learning to learn...

    The move from hand-designed features to learned...

  • A Mathematical Mo...

    Direct democracy, where each voter casts one vo...