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A. Beheshti

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Preprint Sep 2026

Reduce, Then Encode: Multiscale Volumetric Reduction for 2D Foundation Models in Brain MRI

Pretrained 2D foundation models offer a practical alternative to dedicated 3D pretraining for brain structural magnetic resonance imaging (sMRI), but their use on volumetric data requires bridging the mismatch between a 2D encoder and a 3D volume input. Existing methods typically encode slices independently and integra...

De-Xuan Ding, Yuan-Kai Qi, Bo-Gong Wang et al. · 0 citations
Preprint Sep 2026

DementiaCare-Bench: A Modality-Validated Video Benchmark

Dementia affects an estimated 57 million people worldwide, and for most families the hardest part of care is not memory loss but the behavioral and psychological symptoms of dementia (BPSD): agitation, wandering, resistance to care, sundowning. Understanding these symptoms requires more than recognizing the behavior it...

Afrouz Sheikholeslami, Yuan-Kai Qi, Xu-Yun Zhang et al. · 0 citations
Sep 2026

Learning to Adapt: Instance-Level Visual and Semantic Adaptation for Generalized Zero-Shot Learning

Generalized zero-shot learning (GZSL) aims to recognize novel categories by leveraging semantic knowledge transferred from previously observed categories, where learning transferable features for effective visual-semantic alignment plays a critical role. Conventional methods typically utilize all shared attributes to l...

Huajie Jiang, Zheng-Xian Li, Xi-Chao Yu et al. · 0 citations
Open access Sep 2026

Dual Adaptive Visual-Semantic Prompt Collaboration for Generalized Zero-Shot Learning

The Dual Adaptive Visual-Semantic Prompt Collaboration Network (VSPCN+), a novel framework that utilizes prompt-tuning for effective feature adaptation, is proposed, which introduces a dual-prompt mechanism comprising both visual and semantic prompts.

Huajie Jiang, Zheng-Xian Li, Yuankai Qi et al. · 0 citations
Preprint Jul 2026

Harmonised benchmarking of foundation models for single-cell and spatial transcriptomics reveals context-dependent generalisation

This benchmark provides practical guidance for model selection and argues that future models should be judged by biological generalisation, interpretability and perturbation-grounded validity, not by scale or leaderboard performance alone.

S. Chen, Roxana Zahedi, Lucy Chhuo et al. · 0 citations
Review Open access Aug 2026

Auditing Artificial Intelligence Systems: A Survey of Current Frameworks, Principles and Approaches

A systematic review of the literature on methodologies, frameworks, and techniques for auditing AI systems, focusing on legal and ethical considerations and compliance with regulations, reveals gaps in current auditing practices and highlights the importance of incorporating AI value chain stages and AI maturity levels...

Usman Shahbaz, A. Beheshti, B. Abedin et al. · 0 citations

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