With the increasing sophistication of cyber threats, the integration of machine learning (ML)
techniques in network security has become imperative for detecting and mitigating evolving …

Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task, which
focuses on detecting the sentiment polarity towards the aspect in a sentence. However, it is …

The intersection of quantum computing and artificial intelligence (AI) within the cloud
environment represents a paradigm shift in the capabilities of computational technologies …

Relation Extraction (RE) is a crucial task in Information Extraction, which entails predicting
relationships between entities within a given sentence. However, extending pre-trained RE …

Pre-training (PT) and back-translation (BT) are two simple and powerful methods to utilize
monolingual data for improving the model performance of neural machine translation (NMT) …

Text augmentation is a strategy for increasing the diversity of training examples without
explicitly collecting new data. Owing to the efficiency and effectiveness of text augmentation …

We present a simple and effective pretraining strategy {D} en {o} ising {T} raining DoT for
neural machine translation. Specifically, we update the model parameters with source-and …

The multimedia community has shown a significant interest in perceiving and representing
the physical world with multimodal pretrained neural network models, and among them, the …

We introduce Bi-SimCut: a simple but effective training strategy to boost neural machine
translation (NMT) performance. It consists of two procedures: bidirectional pretraining and …

Background: Remote diagnosis using collaborative tools have led to multilingual joint
working sessions in various domains, including comprehensive health care, and resulting in …