7 papers
Rethinking Visual Autoregressive Sampling with Information-Grounding Guidance
Ky Dan Nguyen, Hoang Lam Tran, Anh-Dung Dinh +4
Autoregressive (AR) models based on next-scale prediction have emerged as a powerful tool for image generation, but they face a critical weakness: information inconsistencies betwe…
Learning Topology-Aware Implicit Field for Unified Pulmonary Tree Modeling with Incomplete Topological Supervision
Ziqiao Weng, Jiancheng Yang, Kangxian Xie +2
Pulmonary trees extracted from CT images frequently exhibit topological incompleteness, such as missing or disconnected branches, which substantially degrades downstream anatomical…
FedSKD: Aggregation-free Model-heterogeneous Federated Learning via Multi-dimensional Similarity Knowledge Distillation for Medical Image Classification
Ziqiao Weng, Weidong Cai, Bo Zhou
Federated learning (FL) enables privacy-preserving collaborative model training without direct data sharing. Model-heterogeneous FL (MHFL) extends this paradigm by allowing clients…
Constraining Streaming Flow Models for Adapting Learned Robot Trajectory Distributions
Jieting Long, Dechuan Liu, Weidong Cai +2
Robot motion distributions often exhibit multi-modality and require flexible generative models for accurate representation. Streaming Flow Policies (SFPs) have recently emerged as…
HiFusion: Hierarchical Intra-Spot Alignment and Regional Context Fusion for Spatial Gene Expression Prediction from Histopathology
Ziqiao Weng, Yaoyu Fang, Jiahe Qian +4
Spatial transcriptomics (ST) bridges gene expression and tissue morphology but faces clinical adoption barriers due to technical complexity and prohibitive costs. While computation…
VRM: Knowledge Distillation via Virtual Relation Matching
Weijia Zhang, Fei Xie, Weidong Cai +1
Knowledge distillation (KD) aims to transfer the knowledge of a more capable yet cumbersome teacher model to a lightweight student model. In recent years, relation-based KD methods…