6 citations · 9 across the 17 of their papers we have counts for
17 papers
Latent-CURE for Breast Cancer Diagnosis
Weiyi Zhao, Xiaoyu Tan, Lu Gan +2
Multimodal Large Models have significantly advanced automated breast ultrasound diagnosis. However, most existing frameworks utilize opaque, end-to-end paradigms prioritizing globa…
CW-B: Class Weighted Boosting Framework for Imbalance Resilient Multi Class Cardiac Phenotyping
Sijia Li, Xiaoyu Tan, Chen Zhan +3
Cardiac discharge phenotyping informs post-discharge treatment and follow-up, but real-world records are often incomplete and class-imbalanced, increasing the risk of missed high-r…
VentAgent: When LLMs Learn to Breathe -- Multi-Objective Arbitration for ARDS Ventilation
Teqi Hao, Yuxuan Fu, Xiaoyu Tan +4
Mechanical ventilation for Acute Respiratory Distress Syndrome (ARDS) requires balancing competing physiological goals, including oxygenation, lung protection, and acid-base homeos…
Structured Visual Evidence Decomposition for Evidence-Grounded Multimodal Screening of Obstructive Sleep Apnea-Hypopnea Syndrome
Chen Zhan, Yingchen Wei, Xiaoyu Tan +2
Effective pre-polysomnography screening for obstructive sleep apnea-hypopnea syndrome (OSAHS) requires combining clinical risk factors with visible craniofacial and neck cues. Dire…
Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning
Sijia Li, Xiaoyu Tan, Qixing Wang +7
Ventilator decision support requires sequential decisions that track evolving physiology and disease trajectories while respecting safety boundaries and clinician specific tuning s…
Active Evidence-Seeking and Diagnostic Reasoning in Large Language Models for Clinical Decision Support
Chen Zhan, Xihe Qiu, Xiaoyu Tan +8
Large language models perform well on static medical examinations, yet clinical diagnosis often requires iterative evidence gathering under uncertainty. Building on prior interacti…
From Answers to Arguments: Toward Trustworthy Clinical Diagnostic Reasoning with Toulmin-Guided Curriculum Goal-Conditioned Learning
Chen Zhan, Xiaoyu Tan, Gengchen Ma +3
The integration of Large Language Models (LLMs) into clinical decision support is critically obstructed by their opaque and often unreliable reasoning. In the high-stakes domain of…
VIVID-Med: LLM-Supervised Structured Pretraining for Deployable Medical ViTs
Xiyao Wang, Xiaoyu Tan, Yang Dai +3
Vision-language pretraining has driven significant progress in medical image analysis. However, current methods typically supervise visual encoders using one-hot labels or free-for…
PRISM: Festina Lente Proactivity -- Risk-Sensitive, Uncertainty-Aware Deliberation for Proactive Agents
Yuxuan Fu, Xiaoyu Tan, Teqi Hao +2
Proactive agents must decide not only what to say but also whether and when to intervene. Many current systems rely on brittle heuristics or indiscriminate long reasoning, which of…
Curiosity Driven Knowledge Retrieval for Mobile Agents
Sijia Li, Xiaoyu Tan, Shahir Ali +3
Mobile agents have made progress toward reliable smartphone automation, yet performance in complex applications remains limited by incomplete knowledge and weak generalization to u…
SRUG: A Fusion-Driven Generator Network for Medical Image Translation
Xihe Qiu, Yang Dai, Xiaoyu Tan +4
MRI sequence synthesis aims to recover missing image contrast while preserving patient-specific anatomy. The choice of generation mechanism affects both optimization and the way so…
EEG-VLM: A Hierarchical Vision-Language Model with Multi-Level Feature Alignment and Visually Enhanced Language-Guided Reasoning for EEG Image-Based Sleep Stage Prediction
Xihe Qiu, Gengchen Ma, Haoyu Wang +3
Sleep stage classification based on electroencephalography (EEG) is fundamental for assessing sleep quality and diagnosing sleep-related disorders. However, most traditional machin…
Adaptive Learning on User Segmentation: Universal to Specific Representation via Bipartite Neural Interaction
Xiaoyu Tan, Yongxin Deng, Chao Qu +4
Recently, models for user representation learning have been widely applied in click-through-rate (CTR) and conversion-rate (CVR) prediction. Usually, the model learns a universal u…
CogniDual Framework: Self-Training Large Language Models within a Dual-System Theoretical Framework for Improving Cognitive Tasks
Yongxin Deng, Xihe Qiu, Xiaoyu Tan +5
Cognitive psychology investigates perception, attention, memory, language, problem-solving, decision-making, and reasoning. Kahneman's dual-system theory elucidates the human decis…
FedSlate:A Federated Deep Reinforcement Learning Recommender System
Yongxin Deng, Xihe Qiu, Xiaoyu Tan +1
Reinforcement learning methods have been used to optimize long-term user engagement in recommendation systems. However, existing reinforcement learning-based recommendation systems…
Subequivariant Reinforcement Learning Framework for Coordinated Motion Control
Haoyu Wang, Xiaoyu Tan, Xihe Qiu +1
Effective coordination is crucial for motion control with reinforcement learning, especially as the complexity of agents and their motions increases. However, many existing methods…
PILLOW: Enhancing Efficient Instruction Fine-tuning via Prompt Matching
Zhenting Qi, Xiaoyu Tan, Shaojie Shi +3
Instruction fine-tuning has conventionally been employed to adapt Large Language Models (LLMs) to a variety of tasks. Nonetheless, this technique often necessitates substantial com…