Cross-modal retrieval is an essential area of representation learning, which aims to retrieve
instances with the same semantics from different modalities. In real implementation, a key …

Deep learning classifiers achieve state-of-the-art performance in various risk detection
applications. They explore rich semantic representations and are supposed to automatically …

Semantic Textual Similarity (STS) is an important task in the area of Natural Language
Processing (NLP) that measures the similarity of the underlying semantics of two texts …

Social networks have become venues where people can share and spread hate speech,
especially when the platforms allow users to remain anonymous. Hate speech can have …

As machine learning grows increasingly complex due to big data and deep learning, model
explainability has become essential to fostering user trust. Quantum machine learning …

Out-of-Domain (OOD) text detection has attracted significant research interest. However,
conventional approaches primarily employ Cross-Entropy loss during upstream encoder …

Data augmentation and supervised contrastive learning represent two techniques that
contribute to state-of-the-art performance in image classification. Unfortunately, techniques …