Document-level context for neural machine translation (NMT) is crucial to improve the
translation consistency and cohesion, the translation of ambiguous inputs, as well as several …

In spite of the rapid advancements in unsupervised log anomaly detection techniques, the
current mainstream models still necessitate specific training for individual system datasets …

Named entity recognition (NER) is a fundamental task in natural language processing that
involves identifying and classifying entities in sentences into pre-defined types. It plays a …

Abstract Context-aware Neural Machine Translation can potentially enhance automated
translation quality through effective modelling of context beyond the sentence level …

The field of artificial intelligence has witnessed significant advancements in natural
language processing, largely attributed to the capabilities of Large Language Models …

Training data has a significant impact on the performance of artificial neural network (ANN)
models. This becomes evident when the model is used in a variable environment with input …