The development of deep learning techniques has allowed Neural Machine Translation
(NMT) models to become extremely powerful, given sufficient training data and training time …

Obtaining human-like performance in NLP is often argued to require compositional
generalisation. Whether neural networks exhibit this ability is usually studied by training …

Modern neural machine translation (NMT) models have achieved competitive performance
in standard benchmarks such as WMT. However, there still exist significant issues such as …

Modern neural machine translation (NMT) models have achieved competitive performance
in standard benchmarks. However, they have recently been shown to suffer limitation in …

Neural Machine Translation systems built on top of Transformer-based architectures are
routinely improving the state-of-the-art in translation quality according to word-overlap …

The data-driven paradigm of neural machine translation is a powerful translation technology
based on state-of-the art approaches in artificial intelligence research. This technology is …

Metamorphic testing has recently been used to check the safety of neural NLP models. Its
main advantage is that it does not rely on a ground truth to generate test cases. However …

Complexity theory, complexity philosophy or complexity thinking, whichever way one wants
to look at the development of complexity in scholarly thinking, is suggesting a foundational …

Despite the tremendous success of Neural Machine Translation (NMT), its performance on
low-resource language pairs still remains subpar, partly due to the limited ability to handle …

Large Language Models (LLMs) have been shown to perform well for many downstream
tasks. Transfer learning can enable LLMs to acquire skills that were not targeted during pre …