14 citations · 64 across the 15 of their papers we have counts for
7 papers · 1 filter
SmartAgent: Chain-of-User-Thought for Embodied Personalized Agent in Cyber World
Jiaqi Zhang, Chen Gao, Liyuan Zhang +2
Recent advances in embodied agents with multimodal perception and reasoning capabilities based on large vision-language models (LVLMs), excel in autonomously interacting either rea…
LLM-based Bi-level Multi-interest Learning Framework for Sequential Recommendation
Shutong Qiao, Chen Gao, Wei Yuan +2
Sequential recommendation (SR) leverages users' dynamic preferences, with recent advances incorporating multi-interest learning to model diverse user interests. However, most multi…
EmbodiedCity: A Benchmark Platform for Embodied Agent in Real-world City Environment
Chen Gao, Baining Zhao, Weichen Zhang +9
Embodied artificial intelligence emphasizes the role of an agent's body in generating human-like behaviors. The recent efforts on EmbodiedAI pay a lot of attention to building up m…
Depression Detection on Social Media with Large Language Models
Xiaochong Lan, Zhiguang Han, Yiming Cheng +4
Limited access to mental healthcare resources hinders timely depression diagnosis, leading to detrimental outcomes. Social media platforms present a valuable data source for early…
Identify Critical Nodes in Complex Network with Large Language Models
Jinzhu Mao, Dongyun Zou, Li Sheng +4
Identifying critical nodes in networks is a classical decision-making task, and many methods struggle to strike a balance between adaptability and utility. Therefore, we propose an…
Multi-view Intent Learning and Alignment with Large Language Models for Session-based Recommendation
Shutong Qiao, Wei Zhou, Junhao Wen +4
Session-based recommendation (SBR) methods often rely on user behavior data, which can struggle with the sparsity of session data, limiting performance. Researchers have identified…
Large Language Model Agent for Hyper-Parameter Optimization
Siyi Liu, Chen Gao, Yong Li
Hyperparameter optimization is critical in modern machine learning, requiring expert knowledge, numerous trials, and high computational and human resources. Despite the advancement…