activity
20242026
collaborators

6 papers

cs.AI2026

VitalDiagnosis: AI-Driven Ecosystem for 24/7 Vital Monitoring and Chronic Disease Management

Zhikai Xue, Tianqianjin Lin, Pengwei Yan +4

Chronic diseases have become the leading cause of death worldwide, a challenge intensified by strained medical resources and an aging population. Individually, patients often strug…

cs.CL2025

Teaching According to Students' Aptitude: Personalized Mathematics Tutoring via Persona-, Memory-, and Forgetting-Aware LLMs

Yang Wu, Rujing Yao, Tong Zhang +4

Large Language Models (LLMs) are increasingly integrated into intelligent tutoring systems to provide human-like and adaptive instruction. However, most existing approaches fail to…

cs.AI2025

RAVR: Reference-Answer-guided Variational Reasoning for Large Language Models

Tianqianjin Lin, Xi Zhao, Xingyao Zhang +5

Reinforcement learning (RL) can refine the reasoning abilities of large language models (LLMs), but critically depends on a key prerequisite: the LLM can already generate high-util…

cs.SI2025

Social inequality and cultural factors impact the awareness and reaction during the cryptic transmission period of pandemic

Zhuoren Jiang, Xiaozhong Liu, Yangyang Kang +3

The World Health Organization (WHO) declared the COVID-19 outbreak a Public Health Emergency of International Concern (PHEIC) on January 31, 2020. However, rumors of a "mysterious…

cs.LG2024

LangGFM: A Large Language Model Alone Can be a Powerful Graph Foundation Model

Tianqianjin Lin, Pengwei Yan, Kaisong Song +7

Graph foundation models (GFMs) have recently gained significant attention. However, the unique data processing and evaluation setups employed by different studies hinder a deeper u…

cs.AI2024

Can Large Language Models Grasp Legal Theories? Enhance Legal Reasoning with Insights from Multi-Agent Collaboration

Weikang Yuan, Junjie Cao, Zhuoren Jiang +7

Large Language Models (LLMs) could struggle to fully understand legal theories and perform complex legal reasoning tasks. In this study, we introduce a challenging task (confusing…