Papers with character-based representations

2 papers
Cross-Domain Review Helpfulness Prediction Based on Convolutional Neural Networks with Auxiliary Domain Discriminators (N18-2)

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Challenge: Recent studies on review helpfulness prediction require labeled samples for each domain/category of interest.
Approach: They propose a convolutional neural network based model which leverages word-level and character-based representations to transfer knowledge between domains.
Outcome: The proposed model outperforms the state-of-the-art on the Amazon product review dataset.
One Size Does Not Fit All: Comparing NMT Representations of Different Granularities (N19-1)

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Challenge: Recent work has shown that contextualized word representations are a viable alternative to simple word prediction tasks.
Approach: They propose to use subword units and characters to model morphology, syntax, and semantics instead of word embeddings.
Outcome: The proposed representations are better for modeling syntax and more robust to noisy input.

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