collaborators

15 papers

cs.LG2026

DRIFT: Direct-Recursive Intervention-Conditioned Forecasting of ICU Physiological Trajectories

Weixin Liu, Juming Xiong, Congning Ni +4

Many time-series forecasts depend not only on prior observations but also on actions specified during the forecast period. In intensive care units (ICUs), future vital signs and la…

cs.AI2026

SAGEAgent: A Self-Evolving Agent for Cost-Aware Modality Acquisition in Multimodal Survival Prediction

Chongyu Qu, Can Cui, Zhengyi Lu +8

Does every cancer patient truly need a complete diagnostic workup for accurate survival prediction? In multimodal clinical oncology, diagnostic modalities follow a clinically manda…

cs.CV2026

MORI-Seg: Learning Morphological Geometry for Instance Segmentation without Instance Annotations

Leiyue Zhao, Tianyu Shi, Daniel Reisenbuchler +12

Instance-level quantification of kidney functional units is essential for morphometric analysis, yet most publicly available pathology datasets provide only semantic segmentation a…

cs.CV2026

DUET: Dual-Paradigm Adaptive Expert Triage with Single-cell Inductive Prior for Spatial Transcriptomics Prediction

Junchao Zhu, Ruining Deng, Junlin Guo +11

Inferring spatially resolved gene expression from histology images offers a cost-effective complement to spatial transcriptomics (ST). However, existing methods reduce this task to…

cs.CV2026

VIP: Visual-guided Prompt Evolution for Efficient Dense Vision-Language Inference

Hao Zhu, Shuo Jin, Wenbin Liao +4

Pursuing training-free open-vocabulary semantic segmentation in an efficient and generalizable manner remains challenging due to the deep-seated spatial bias in CLIP. To overcome t…

cs.CV2026

Explainable Pathomics Feature Visualization via Correlation-aware Conditional Feature Editing

Yuechen Yang, Junlin Guo, Ruining Deng +9

Pathomics is a recent approach that offers rich quantitative features beyond what black-box deep learning can provide, supporting more reproducible and explainable biomarkers in di…