Unpaired cross-lingual image captioning has long suffered from irrelevancy and disfluency
issues, due to the inconsistencies of the semantic scene and syntax attributes during …

Large language models (LLMs) have shown great potential in domain-specific machine
translation (MT). However, one major issue is that LLMs pre-trained on general domain …

In recent years, people have preferred interacting on social media instead of physical
meetings. Researchers have explored social media text data to predict user personality …

With great practical value, the study of Multi-domain Neural Machine Translation (NMT)
mainly focuses on using mixed-domain parallel sentences to construct a unified model that …

Cross-lingual text classification (CLTC) is the task of classifying documents written in
different languages into the same taxonomy of categories. This paper presents a novel …

Bertalign is designed to improve sentence alignment accuracy for Chinese–English parallel
corpora of literary texts. Aligning bilingual literary texts is not trivial, since most of the …

Domain Adaptation is widely used in practical applications of neural machine translation,
which aims to achieve good performance on both the general-domain and in-domain …

Neural machine translation often adopts the fine-tuning approach to adapt to specific
domains. However, nonrestricted fine-tuning can easily degrade on the general domain and …

Parallel corpora can be defined as collections of aligned, translated texts of two or more
languages. They play a major role in translation and contrastive studies, and are also …

Owing to its practical significance, multi-domain Neural Machine Translation (NMT) has
attracted much attention recently. Recent studies mainly focus on constructing a unified NMT …