Data-driven and machine learning based approaches for detecting, categorising and
measuring abusive content such as hate speech and harassment have gained traction due …

Recent natural language processing (NLP) techniques have accomplished high
performance on benchmark data sets, primarily due to the significant improvement in the …

The way users acquire information is undergoing a paradigm shift with the advent of
ChatGPT. Unlike conventional search engines, ChatGPT retrieves knowledge from the …

A robust evaluation metric has a profound impact on the development of text generation
systems. A desirable metric compares system output against references based on their …

Adversarial attacks are carried out to reveal the vulnerability of deep neural networks.
Textual adversarial attacking is challenging because text is discrete and a small perturbation …

Adversarial attacks and backdoor attacks are two common security threats that hang over
deep learning. Both of them harness task-irrelevant features of data in their implementation …

Robustness against word substitutions has a well-defined and widely acceptable form, ie,
using semantically similar words as substitutions, and thus it is considered as a fundamental …

Textual adversarial attacking has received wide and increasing attention in recent years.
Various attack models have been proposed, which are enormously distinct and …

Semantic parsing is a technique aimed at constructing a structured representation of the
meaning of a natural-language question. Recent advancements in few-shot language …

Obstacles hindering the development of capsule networks for challenging NLP applications
include poor scalability to large output spaces and less reliable routing processes. In this …