Papers with lattice-based encoders

1 papers
Lattice-Based Transformer Encoder for Neural Machine Translation (P19-1)

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Challenge: Neural machine translation (NMT) takes deterministic sequences for source representations. However, word-level or subword-level segmentation has multiple choices to split a source sequence with different word segmentors or different subword vocabulary sizes.
Approach: They propose lattice-based encoders to explore effective word or subword representations in an automatic way during training.
Outcome: The proposed encoders can explore effective word or subword representation in an automatic way during training.

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