11 papers
A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks
Silin Chen, Yuzhong Chen, Caiwei Wang +9
Whether artificial neural networks organize information comparably to the human brain remains unclear. Prior brain--AI alignment studies are constrained by specific inputs and task…
Layer-Specific Prompt Fusion Discovery via Differentiable Search in Vision Foundation Models
Xi Xiao, Xingjian Li, Yunbei Zhang +7
Visual prompt tuning has emerged as a parameter-efficient fine-tuning approach for adapting large-scale Vision Transformers (ViTs) to downstream tasks. As its learnable prompts are…
MedVIGIL: Evaluating Trustworthy Medical VLMs Under Broken Visual Evidence
Hanqi Jiang, Junhao Chen, Mingyu Kang +12
Medical vision--language models (VLMs) are usually evaluated on intact image--question pairs, but trustworthy clinical use requires a stronger property: a model must recognise when…
A World Model of Radiologist Reading for Medical Image Representation Learning
Yiwei Li, Zihao Wu, Huaqin Zhao +5
Radiologist eye-tracking data provide a rich record of how experts search, compare, and accumulate evidence during image reading; yet, existing methods exploit this signal only par…
Conditional Evidence Reconstruction and Decomposition for Interpretable Multimodal Diagnosis
Shaowen Wan, Yanjun Lv, Lu Zhang +5
Neurobiological and neurodegenerative diseases are inherently multifactorial, arising from coupled influences spanning genetic susceptibility, brain alterations, and environmental…
IMA-MoE: An Interpretable Modality-Aware Mixture-of-Experts Framework for Characterizing the Neurobiological Signatures of Binge Eating Disorder
Lin Zhao, Qiaohui Gao, Elizabeth Martin +5
Binge eating disorder (BED) is the most prevalent eating disorder. However, current diagnostic frameworks remain largely grounded in symptom-based criteria rather than underlying b…