Papers with RNN layer

2 papers
Transformation Networks for Target-Oriented Sentiment Classification (P18-1)

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Challenge: a new model for sentiment classification uses attention instead of attention to classify sentiment polarities over individual opinion targets.
Approach: They propose a model that uses a CNN layer to extract salient features from transformed word representations from a bi-directional RNN layer.
Outcome: The proposed model achieves state-of-the-art on a few benchmarks.
Direct Output Connection for a High-Rank Language Model (D18-1)

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Challenge: Neural network language models have played a central role in recent natural language processing advances.
Approach: They propose a recurrent neural network language model that combines probability distributions computed from a final RNN layer and also middle layers.
Outcome: The proposed language model achieves the best score on the Penn Treebank and WikiText-2 benchmark datasets.

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