IEEE transactions on visualization and computer graphics
Nov 25, 2024
Synthetic Lethal (SL) relationships, though rare among the vast array of gene combinations, hold substantial promise for targeted cancer therapy. Despite advancements in AI model accuracy, there is still a significant need among domain experts for in...
IEEE transactions on visualization and computer graphics
Nov 25, 2024
Large Language Models (LLMs) have been adopted for a variety of visualizations tasks, but how far are we from perceptually aware LLMs that can predict human takeaways? Graphical perception literature has shown that human chart takeaways are sensitive...
IEEE transactions on visualization and computer graphics
Nov 25, 2024
Large Language Models (LLMs) are powerful but also raise significant security concerns, particularly regarding the harm they can cause, such as generating fake news that manipulates public opinion on social media and providing responses to unethical ...
IEEE transactions on visualization and computer graphics
Nov 25, 2024
In this study, we address the growing issue of misleading charts, a prevalent problem that undermines the integrity of information dissemination. Misleading charts can distort the viewer's perception of data, leading to misinterpretations and decisio...
IEEE transactions on visualization and computer graphics
Nov 25, 2024
The concept of an intelligent augmented reality (AR) assistant has significant, wide-ranging applications, with potential uses in medicine, military, and mechanics domains. Such an assistant must be able to perceive the environment and actions, reaso...
IEEE transactions on visualization and computer graphics
Nov 25, 2024
Recent advancements in Large Language Models (LLMs) and Prompt Engineering have made chatbot customization more accessible, significantly reducing barriers to tasks that previously required programming skills. However, prompt evaluation, especially a...
Neural networks : the official journal of the International Neural Network Society
Nov 22, 2024
Due to the neighborhood explosion phenomenon, scaling up graph neural networks to large graphs remains a huge challenge. Various sampling-based mini-batch approaches, such as node-wise, layer-wise, and subgraph sampling, have been proposed to allevia...
Neural networks : the official journal of the International Neural Network Society
Oct 24, 2024
Recently, recommending bundles - sets of items that complement each other - instead of individual items to users has drawn much attention in both academia and industry. Models based on Graph Neural Networks (GNNs) for bundle recommendation have achie...
Journal of chemical information and modeling
Oct 23, 2024
Graph neural networks (GNNs) have revolutionized drug discovery in chemistry and biology, enhancing efficiency and reducing resource demands. However, classical GNNs often struggle to capture long-range dependencies due to challenges like oversmoothi...
Neural networks : the official journal of the International Neural Network Society
Oct 21, 2024
Graphs are ubiquitous in real-world applications, such as computation graphs and social networks. Partitioning large graphs into smaller, balanced partitions is often essential, with the bi-objective graph partitioning problem aiming to minimize both...