Small data are often used in scientific and engineering research due to the presence of
various constraints, such as time, cost, ethics, privacy, security, and technical limitations in …

Transformer is a promising neural network learner, and has achieved great success in
various machine learning tasks. Thanks to the recent prevalence of multimodal applications …

In our digital age, data are generated constantly from public and private sources, social
media platforms, and the Internet of Things. A significant portion of this information comes in …

Food recognition plays an important role in food choice and intake, which is essential to the
health and well‐being of humans. It is thus of importance to the computer vision community …

Transformers have demonstrated remarkable accomplishments in several natural language
processing (NLP) tasks as well as image processing tasks. Herein, we present a deep …

In this paper, we are interested in modeling a how-to instructional procedure, such as a
cooking recipe, with a meaningful and rich high-level representation. Specifically, we …

Current mainstream vision-language (VL) tracking framework consists of three parts, ie, a
visual feature extractor, a language feature extractor, and a fusion model. To pursue better …

Designed to establish potential relations and distill high-order representations, graph-based
recommendation systems continue to reveal promising results by jointly modeling ratings …

With the rapid development of online recipe sharing platforms, food recommendation is
emerging as an important application. Although recent studies have made great progress on …

Review-based recommender systems explore semantic aspects of users' preferences by
incorporating user-generated reviews into rating-based models. Recent works have …