1 citations · 1 across the 4 of their papers we have counts for
6 papers
Robust Reinforcement Learning for Dynamic Treatment Regimes under Model and Measurement Uncertainty
Chengze Xie, Xuan Wang, Ying Ding +2
We develop a robust reinforcement learning (RL) framework for learning adaptive treatment policies that generalize across patients and remain reliable under errors in the measured…
SEER: Long-Context Reasoning via Selective Visual-Text Compression
Jiawei Xu, Zhilin Zhai, Jinrui Fang +6
Long-context reasoning remains computationally expensive for large language models due to the quadratic complexity of attention over text tokens. Visual-text compression offers a p…
Chreode: A Cell World Model for One-Step Temporal Dynamics and Perturbation Prediction
Mufan Qiu, Genhui Zheng, Yinuo Xu +4
Predicting how a cell will change its transcriptional state under a developmental signal or a genetic perturbation is the computational core of in-silico biology and the AI Virtual…
ConceptMoE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational Pathology
Xuan Wang, Zhongling Xu, Gopi Kannedhara +13
Healthcare models are transitioning from unimodal prediction toward multimodal reasoning over heterogeneous diagnostic inputs. In computational pathology, for complex tumor subtype…
Clinically-Informed Modeling for Pediatric Brain Tumor Classification from Whole-Slide Histopathology Images
Joakim Nguyen, Jian Yu, Jinrui Fang +7
Accurate diagnosis of pediatric brain tumors, starting with histopathology, presents unique challenges for deep learning, including severe data scarcity, class imbalance, and fine-…
Mapping from Meaning: Addressing the Miscalibration of Prompt-Sensitive Language Models
Kyle Cox, Jiawei Xu, Yikun Han +6
An interesting behavior in large language models (LLMs) is prompt sensitivity. When provided with different but semantically equivalent versions of the same prompt, models may prod…