arXiv:2512.01037v2 Announce Type: replace-cross Abstract: Safety-aligned language models often refuse prompts that are actually harmless. Current evaluations mostly report global rates such as false rejection or compliance. These scores treat each prompt alone and miss local inconsistency, where a model accepts one phrasing of an intent but rejects a close paraphrase. This gap limits diagnosis […]
A unified FLAIR hyperintensity segmentation model for various CNS tumor types and acquisition time points
arXiv:2512.17566v1 Announce Type: cross Abstract: T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) scans are important for diagnosis, treatment planning and monitoring of brain tumors. Depending on the brain tumor type, the FLAIR hyperintensity volume is an important measure to asses the tumor volume or surrounding edema, and an automatic segmentation of this would […]
Weighted Stochastic Differential Equation to Implement Wasserstein-Fisher-Rao Gradient Flow
arXiv:2512.17878v1 Announce Type: cross Abstract: Score-based diffusion models currently constitute the state of the art in continuous generative modeling. These methods are typically formulated via overdamped or underdamped Ornstein–Uhlenbeck-type stochastic differential equations, in which sampling is driven by a combination of deterministic drift and Brownian diffusion, resulting in continuous particle trajectories in the ambient space. […]
CLAReSNet: When Convolution Meets Latent Attention for Hyperspectral Image Classification
arXiv:2511.12346v2 Announce Type: replace-cross Abstract: Hyperspectral image (HSI) classification faces critical challenges, including high spectral dimensionality, complex spectral-spatial correlations, and limited training samples with severe class imbalance. While CNNs excel at local feature extraction and transformers capture long-range dependencies, their isolated application yields suboptimal results due to quadratic complexity and insufficient inductive biases. We propose […]
OntoGSN: An Ontology-Based Framework for Semantic Management and Extension of Assurance Cases
arXiv:2506.11023v2 Announce Type: replace Abstract: Assurance cases (ACs) are a common artifact for building and maintaining confidence in system properties such as safety or robustness. Constructing an AC can be challenging, although existing tools provide support in static, document-centric applications and methods for dynamic contexts (e.g., autonomous driving) are emerging. Unfortunately, managing ACs remains a […]
When De-noising Hurts: A Systematic Study of Speech Enhancement Effects on Modern Medical ASR Systems
arXiv:2512.17562v1 Announce Type: cross Abstract: Speech enhancement methods are commonly believed to improve the performance of automatic speech recognition (ASR) in noisy environments. However, the effectiveness of these techniques cannot be taken for granted in the case of modern large-scale ASR models trained on diverse, noisy data. We present a systematic evaluation of MetricGAN-plus-voicebank denoising […]
Quantum Generative Modeling of Single-Cell transcriptomes: Capturing Gene-Gene and Cell-Cell Interactions
arXiv:2510.12776v3 Announce Type: replace Abstract: Single-cell RNA sequencing (scRNA-seq) data simulation is limited by classical methods that rely on linear correlations, failing to capture the intrinsic, nonlinear dependencies. No existing simulator jointly models gene-gene and cell-cell interactions. We introduce qSimCells, a novel quantum computing-based simulator that employs entanglement to model intra- and inter-cellular interactions, generating […]
Semi-Supervised Preference Optimization with Limited Feedback
arXiv:2511.00040v2 Announce Type: replace-cross Abstract: The field of preference optimization has made outstanding contributions to the alignment of language models with human preferences. Despite these advancements, recent methods still rely heavily on substantial paired (labeled) feedback data, leading to substantial resource expenditures. To address these challenges, we study the problem of Semi-Supervised Preference Optimization (SSPO) […]
An AI-driven Assessment of Bone Density as a Biomarker Leading to the Aging Law
arXiv:2308.02815v2 Announce Type: replace-cross Abstract: As global population aging intensifies, there is growing interest in the study of biological age. Bones have long been used to evaluate biological age, and the decline in bone density with age is a well-recognized phenomenon in adults. However, the pattern of this decline remains controversial, making it difficult to […]
ClothHMR: 3D Mesh Recovery of Humans in Diverse Clothing from Single Image
arXiv:2512.17545v1 Announce Type: cross Abstract: With 3D data rapidly emerging as an important form of multimedia information, 3D human mesh recovery technology has also advanced accordingly. However, current methods mainly focus on handling humans wearing tight clothing and perform poorly when estimating body shapes and poses under diverse clothing, especially loose garments. To this end, […]