Deep learning--based models have surpassed classical machine learning--based
approaches in various text classification tasks, including sentiment analysis, news …

Deep learning models have achieved great success in solving a variety of natural language
processing (NLP) problems. An ever-growing body of research, however, illustrates the …

Natural language inference (NLI) is the task of determining if a natural language hypothesis
can be inferred from a given premise in a justifiable manner. NLI was proposed as a …

Fact verification (FV) is a challenging task which requires to retrieve relevant evidence from
plain text and use the evidence to verify given claims. Many claims require to simultaneously …

Modeling natural language inference is a very challenging task. With the availability of large
annotated data, it has recently become feasible to train complex models such as neural …

The ability to generalise well is one of the primary desiderata of natural language
processing (NLP). Yet, what'good generalisation'entails and how it should be evaluated is …

For years, recursive neural networks (RvNNs) have been shown to be suitable for
representing text into fixed-length vectors and achieved good performance on several …