activity
20242026
collaborators

12 papers

cs.DL2026

Lishu: A Real-Source Research Workbench for Elite Business Journal Search, Analysis, and Writing Support

Chuang Zhao, Hongke Zhao, Yichen Li +2

This paper presents Lishu, a deployable web artifact for searching, monitoring, and interpreting literature from elite business and management journals. The system integrates the U…

q-bio.QM2026

From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning

Chuang Zhao, Hongke Zhao, Xiaofang Zhou +1

Contextual clinical reasoning demands robust inference grounded in complex, heterogeneous clinical records. While state-of-the-art fine-tuning, in-context learning (ICL), and retri…

q-bio.OT2025

Reinventing Clinical Dialogue: Agentic Paradigms for LLM Enabled Healthcare Communication

Xiaoquan Zhi, Hongke Zhao, Likang Wu +2

Clinical dialogue represents a complex duality requiring both the empathetic fluency of natural conversation and the rigorous precision of evidence-based medicine. While Large Lang…

cs.AI2025

Grounded by Experience: Generative Healthcare Prediction Augmented with Hierarchical Agentic Retrieval

Chuang Zhao, Hui Tang, Hongke Zhao +2

Accurate healthcare prediction is critical for improving patient outcomes and reducing operational costs. Bolstered by growing reasoning capabilities, large language models (LLMs)…

cs.LG2025

Diffmv: A Unified Diffusion Framework for Healthcare Predictions with Random Missing Views and View Laziness

Chuang Zhao, Hui Tang, Hongke Zhao +1

Advanced healthcare predictions offer significant improvements in patient outcomes by leveraging predictive analytics. Existing works primarily utilize various views of Electronic…

cs.CL2025

Instruct-of-Reflection: Enhancing Large Language Models Iterative Reflection Capabilities via Dynamic-Meta Instruction

Liping Liu, Chunhong Zhang, Likang Wu +4

Self-reflection for Large Language Models (LLMs) has gained significant attention. Existing approaches involve models iterating and improving their previous responses based on LLMs…