Self contrastive learning for session-based recommendation
Session-based recommendation, which aims to predict the next item of users' interest as per
an existing sequence interaction of items, has attracted growing applications of Contrastive …
an existing sequence interaction of items, has attracted growing applications of Contrastive …
Multimodal Learned Sparse Retrieval for Image Suggestion
T Nguyen, M Hendriksen, A Yates - arXiv preprint arXiv:2402.07736, 2024 - arxiv.org
Learned Sparse Retrieval (LSR) is a group of neural methods designed to encode queries
and documents into sparse lexical vectors. These vectors can be efficiently indexed and …
and documents into sparse lexical vectors. These vectors can be efficiently indexed and …
Rethink the Effectiveness of Text Data Augmentation: An Empirical Analysis
In recent years, language models (LMs) have made remarkable progress in advancing the
field of natural language processing (NLP). However, the impact of data augmentation (DA) …
field of natural language processing (NLP). However, the impact of data augmentation (DA) …
Eigenvector-based graph neural network embeddings and trust rating prediction in bitcoin networks
Given their strong performance on a variety of graph learning tasks, Graph Neural Networks
(GNNs) are increasingly used to model financial networks. Traditional GNNs, however, are …
(GNNs) are increasingly used to model financial networks. Traditional GNNs, however, are …