4 accepted papers
Generating high-quality question–answer (QA) pairs for specialized technical domains is essential for advancing knowledge comprehension, yet remains challenging. Existing methods often yield generic or shallow questions that fail to reflect the depth and structure of expert-written examples. We prop
Diffusion models learn to denoise data and the trained denoiser is then used to generate new samples from the data distribution. In this paper, we revisit the diffusion sampling process and identify a fundamental cause of sample quality degradation: the denoiser is poorly estimated in regions that…
Graph neural networks (GNNs) are prominent in the graph machine learning domain, owing to their strong performance across various tasks. A recent focal area is the space of graph self-supervised learning (SSL), which aims to derive useful node representations without labeled data. Notably, many stat…
Multilinear analysis is pervasive in a wide variety of fields, ranging from Signal Processing to Chemometrics, and from Machine Vision to Data Mining. Determining the quality of a given tensor decomposition is a task of utmost importance that spans all fields of application of tensors. This task by…