Abstract Machine reading comprehension (MRC) is a challenging task in the field of artificial
intelligence. Most existing MRC works contain a semantic matching module, either explicitly …

Improvement of software development methodologies attracts developers to automatic
Requirement Formalisation (RF) in the Requirement Engineering (RE) field. The potential …

The long-standing one-to-many issue of the open-domain dialogues poses significant
challenges for automatic evaluation methods, ie, there may be multiple suitable responses …

Large scale adoption of large language models has introduced a new era of convenient
knowledge transfer for a slew of natural language processing tasks. However, these models …

As the demand for highly secure and dependable lightweight systems increases in the
modern world, Physically Unclonable Functions (PUFs) continue to promise a lightweight …

Generating knowledge grounded responses in both goal and non-goal oriented dialogue
systems is an important research challenge. Knowledge Graphs (KG) can be viewed as an …

Variational autoencoders (VAEs) are one of the most powerful unsupervised learning
frameworks in NLP for latent representation learning and latent-directed generation. The …

Understanding speaker's feelings and producing appropriate responses with emotion
connection is a key communicative skill for empathetic dialogue systems. In this paper, we …

Representations from common pre-trained language models have been shown to suffer
from the degeneration problem, ie, they occupy a narrow cone in latent space. This problem …

The widespread use of pre-trained language models has revolutionised knowledge transfer
in natural language processing tasks. However, there is a concern regarding potential …