activity
20242026
most citedCross-domain Transfer of Valence Preferences via a Meta-optimization Approach

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

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…

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.LG2025

Unveiling Discrete Clues: Superior Healthcare Predictions for Rare Diseases

Chuang Zhao, Hui Tang, Jiheng Zhang +1

Accurate healthcare prediction is essential for improving patient outcomes. Existing work primarily leverages advanced frameworks like attention or graph networks to capture the in…

cs.IR2024★ 1 cited

Collaborative Knowledge Fusion: A Novel Approach for Multi-task Recommender Systems via LLMs

Chuang Zhao, Xing Su, Ming He +3

Owing to the impressive general intelligence of large language models (LLMs), there has been a growing trend to integrate them into recommender systems to gain a more profound insi…

cs.IR2024★ 1 cited

Cross-domain Transfer of Valence Preferences via a Meta-optimization Approach

Chuang Zhao, Hongke Zhao, Ming He +2

Cross-domain recommendation offers a potential avenue for alleviating data sparsity and cold-start problems. Embedding and mapping, as a classic cross-domain research genre, aims t…