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…
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…
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…
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…