Paraphrase identification involves identifying whether a pair of sentences express the same
or similar meanings. While cross-encoders have achieved high performances across …

Semantic matching plays a critical role in many downstream tasks of natural language
processing. Existing semantic matching methods, which focus on learning sentence …

Previous works have demonstrated the effectiveness of utilising pre-trained sentence
encoders based on their sentence representations for meaning comparison tasks. Though …

In English semantic similarity tasks, classic word embedding-based approaches explicitly
model pairwise" interactions" between the word representations of a sentence pair …

Medical errors are a major public health concern and a leading cause of death worldwide.
Many healthcare centers and hospitals use reporting systems where medical practitioners …

Semantic text similarity in NLP is the study of the degree of resemblance between texts
using a certain metric. It has many applications in tasks such as question answering …

Chinese text matching is an important task in natural language processing research, but the
current techniques have problems in text feature extraction, such as insufficient word …

In natural language processing (NLP), accurately calculating relatedness scores between
pairs of sentences has significant implications for various tasks, such as information retrieval …

Supervised machine learning methods that use neural networks (“deep learning”) have
yielded substantial improvements to a multitude of Natural Language Processing (NLP) …

This thesis is concerned with the identification of semantic equivalence between pairs of
natural language sentences, by studying and computing models to address Natural …