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Evaluating Hierarchical Document Categorisation
Hierarchical document categorisation is a special case of multi-label document categorisation, where there is a taxonomic hierarchy among the labels.
Auxiliary Learning for Named Entity Recognition with Multiple Auxiliary Biomedical Training Data
As one of the NER improvement approaches, multi-task learning that learns a model from multiple training data has been used.
On the (In)Effectiveness of Images for Text Classification
Images are core components of multi-modal learning in natural language processing (NLP), and results have varied substantially as to whether images improve NLP tasks or not.
Improving Neural Machine Translation with Neural Syntactic Distance
The explicit use of syntactic information has been proved useful for neural machine translation (NMT).
Forest-Based Neural Machine Translation
Tree-based neural machine translation (NMT) approaches, although achieved impressive performance, suffer from a major drawback: they only use the 1-best parse tree to direct the translation, which potentially introduces translation mistakes due to parsing errors.
