Papers with R-NET

1 papers
The Lower The Simpler: Simplifying Hierarchical Recurrent Models (N19-1)

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Challenge: Using a simplified version of GRU, we replace the GRUs at the middle layers of hierarchical recurrent models with Fixed-size Ordinally-Forgetting Encoding (FOFE).
Approach: They propose to make the lower layers simpler than the upper ones to simplify two typical hierarchical recurrent models, namely Hierarchical Recurrent Encoder-Decoder (HRED) and R-NET, whose basic building block is GRU.
Outcome: The proposed models contain less trainable parameters, consume less training time, and achieve slightly better performance than baseline models.

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