6 papers
PathAR: Structure-First Autoregressive Synthesis of Multimodal Pathology Images
Yuan Zhang, Jiahao Xia, Junzhang Huang +4
Data scarcity in multimodal pathology motivates unified generative models that synthesize modality-specific appearance while preserving anatomically coherent structure. Although mo…
Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
Wanghan Xu, Yuhao Zhou, Yifan Zhou +104
Despite advances in scientific AI, a coherent framework for Scientific General Intelligence (SGI)-the ability to autonomously conceive, investigate, and reason across scientific do…
Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges
Yuan Zhang, Xinfeng Zhang, Xiaoming Qi +4
Content generation modeling has emerged as a promising direction in computational pathology, offering capabilities such as data-efficient learning, synthetic data augmentation, and…
PathFL: Multi-Alignment Federated Learning for Pathology Image Segmentation
Yuan Zhang, Feng Chen, Yaolei Qi +2
Pathology image segmentation across multiple centers encounters significant challenges due to diverse sources of heterogeneity including imaging modalities, organs, and scanning eq…
Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for Federated Continual Learning
Xiaoming Qi, Jingyang Zhang, Huazhu Fu +3
Federated continual learning (FCL) offers an emerging pattern to facilitate the applicability of federated learning (FL) in real-world scenarios, where tasks evolve dynamically and…
Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for FCL
Xiaoming Qi, Jingyang Zhang, Huazhu Fu +3
Federated continual learning (FCL) offers an emerging pattern to facilitate the applicability of federated learning (FL) in real-world scenarios, where tasks evolve dynamically and…