Generative object compositing emerges as a promising new avenue for compositional
image editing. However the requirement of object identity preservation poses a significant …

Gastrointestinal (GI) tract disorders, ranging from benign polyps to aggressive forms of
cancer, pose significant health challenges globally. Early detection and precise …

Inverse Uncertainty Quantification (IUQ) method has been widely used to quantify the
uncertainty of Physical Model Parameters (PMPs) in nuclear Thermal Hydraulics (TH) …

Recent advancements in Large Language Models (LLMs) and Prompt Engineering have
made chatbot customization more accessible, significantly reducing barriers to tasks that …

Recent studies seek to provide Graph Neural Network (GNN) interpretability via multiple
unsupervised learning models. Due to the scarcity of datasets, current methods easily suffer …

Large language models are well-known to be effective at few-shot in-context learning (ICL).
Recent advancements in multimodal foundation models have enabled unprecedentedly …

Text-to-video generation has been dominated by end-to-end diffusion-based or
autoregressive models. On one hand, those novel models provide plausible versatility, but …

Personalized image generation has emerged from the recent advancements in generative
models. However, these generated personalized images often suffer from localized artifacts …

The rapid evolution of text-to-image diffusion models has opened the door of generative AI,
enabling the translation of textual descriptions into visually compelling images with …

In the framework of BEPU (Best Estimate plus Uncertainty) methodology, the uncertainties
involved in the simulations must be quantified to prove that the investigated design is …