4 papers
Think before Recommendation: Autonomous Reasoning-enhanced Recommender
Xiaoyu Kong, Junguang Jiang, Bin Liu +6
The core task of recommender systems is to learn user preferences from historical user-item interactions. With the rapid development of large language models (LLMs), recent researc…
Reinforced Preference Optimization for Recommendation
Junfei Tan, Yuxin Chen, An Zhang +7
Recent breakthroughs in large language models (LLMs) have fundamentally shifted recommender systems from discriminative to generative paradigms, where user behavior modeling is ach…
WiS Platform: Enhancing Evaluation of LLM-Based Multi-Agent Systems Through Game-Based Analysis
Chengwei Hu, Jianhui Zheng, Yancheng He +7
Recent advancements in autonomous multi-agent systems (MAS) based on large language models (LLMs) have enhanced the application scenarios and improved the capability of LLMs to han…
Large Language Model as Universal Retriever in Industrial-Scale Recommender System
Junguang Jiang, Yanwen Huang, Bin Liu +6
In real-world recommender systems, different retrieval objectives are typically addressed using task-specific datasets with carefully designed model architectures. We demonstrate t…