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Found 6 papers, 2 papers with code
Enhancing Cross-lingual Transfer by Manifold Mixup
Based on large-scale pre-trained multilingual representations, recent cross-lingual transfer methods have achieved impressive transfer performances.
Combining Character and Word Information in Neural Machine Translation Using a Multi-Level Attention
Natural language sentences, being hierarchical, can be represented at different levels of granularity, like words, subwords, or characters.
Improved Neural Machine Translation with a Syntax-Aware Encoder and Decoder
Most neural machine translation (NMT) models are based on the sequential encoder-decoder framework, which makes no use of syntactic information.
Top-Rank Enhanced Listwise Optimization for Statistical Machine Translation
We propose a listwise learning framework for structure prediction problems such as machine translation.
Non-linear Learning for Statistical Machine Translation
The linear combination assumes that all the features are in a linear relationship and constrains that each feature interacts with the rest features in an linear manner, which might limit the expressive power of the model and lead to a under-fit model on the current data.
