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

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

collaborators

6 papers

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

Recall-Extend Dynamics: Enhancing Small Language Models through Controlled Exploration and Refined Offline Integration

Zhong Guan, Likang Wu, Hongke Zhao +2

Many existing studies have achieved significant improvements in the reasoning capabilities of large language models (LLMs) through reinforcement learning with verifiable rewards (R…

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.AI2025★ 1 cited

Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data

Zhong Guan, Likang Wu, Hongke Zhao +2

Attention mechanisms are critical to the success of large language models (LLMs), driving significant advancements in multiple fields. However, for graph-structured data, which req…

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…