6 papers
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…
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…
A Survey of Large Language Model Empowered Agents for Recommendation and Search: Towards Next-Generation Information Retrieval
Yu Zhang, Shutong Qiao, Jiaqi Zhang +3
Information technology has profoundly altered the way humans interact with information. The vast amount of content created, shared, and disseminated online has made it increasingly…
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…
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…
Enhancing ID-based Recommendation with Large Language Models
Lei Chen, Chen Gao, Xiaoyi Du +4
Large Language Models (LLMs) have recently garnered significant attention in various domains, including recommendation systems. Recent research leverages the capabilities of LLMs t…