collaborators

7 papers

cs.HC2026

EmoPatient: An Emotion-Directed Patient Simulator for Realistic Palliative Care Communication Training

Yining Wu, Tianshu Du, Jinrui Fang +3

Effective communication during palliative care discussions is a critical clinical skill, yet training clinicians to manage complex patient emotions remains challenging. Large langu…

cs.CL2026

No Hidden Prompts Needed! You Can Game AI Peer Review with Presentation-Only Revisions

Xu Yang, Zhizhou Sha, Junbo Li +10

As AI-generated reviews move from experimental tools into peer-review infrastructure, most robustness concerns have focused on explicit attacks such as hidden instructions and prom…

cs.AI2026

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…

cs.CV2026

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-…

cs.CL2026

Benchmarking Multi-turn Medical Diagnosis: Hold, Lure, and Self-Correction

Jinrui Fang, Runhan Chen, Xu Yang +9

Large language models (LLMs) achieve high accuracy in medical diagnosis when all clinical information is provided in a single turn, yet how they behave under multi-turn evidence ac…

cs.CV2026

PathMoE: Interpretable Multimodal Interaction Experts for Pediatric Brain Tumor Classification

Jian Yu, Joakim Nguyen, Jinrui Fang +10

Accurate classification of pediatric central nervous system tumors remains challenging due to histological complexity and limited training data. While pathology foundation models h…