Only 5% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation
Zihan Liu,
Zewei Sun,
Shanbo Cheng
et al.
Abstract:Document-level Neural Machine Translation (DocNMT) has been proven crucial for handling discourse phenomena by introducing document-level context information. One of the most important directions is to input the whole document directly to the standard Transformer model. In this case, efficiency becomes a critical concern due to the quadratic complexity of the attention module. Existing studies either focus on the encoder part, which cannot be deployed on sequence-to-sequence generation tasks, e.g., Machine Tra… Show more
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