3 citations · 7 across the 14 of their papers we have counts for
14 papers
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…
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…
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…
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)…
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…
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…
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…
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…
GANPrompt: Enhancing Robustness in LLM-Based Recommendations with GAN-Enhanced Diversity Prompts
Xinyu Li, Chuang Zhao, Hongke Zhao +2
In recent years, Large Language Models (LLMs) have demonstrated remarkable proficiency in comprehending and generating natural language, with a growing prevalence in the domain of…
MobileExperts: A Dynamic Tool-Enabled Agent Team in Mobile Devices
Jiayi Zhang, Chuang Zhao, Yihan Zhao +3
The attainment of autonomous operations in mobile computing devices has consistently been a goal of human pursuit. With the development of Large Language Models (LLMs) and Visual L…
Performative Debias with Fair-exposure Optimization Driven by Strategic Agents in Recommender Systems
Zhichen Xiang, Hongke Zhao, Chuang Zhao +2
Data bias, e.g., popularity impairs the dynamics of two-sided markets within recommender systems. This overshadows the less visible but potentially intriguing long-tail items that…
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…
Bi-discriminator Domain Adversarial Neural Networks with Class-Level Gradient Alignment
Chuang Zhao, Hongke Zhao, Hengshu Zhu +4
Unsupervised domain adaptation aims to transfer rich knowledge from the annotated source domain to the unlabeled target domain with the same label space. One prevalent solution is…
Cross-domain recommendation via user interest alignment
Chuang Zhao, Hongke Zhao, Ming He +2
Cross-domain recommendation aims to leverage knowledge from multiple domains to alleviate the data sparsity and cold-start problems in traditional recommender systems. One popular…