10 papers
Generative Multi-Target Cross-Domain Recommendation
Jinqiu Jin, Yang Zhang, Fuli Feng +1
Recently, there has been a surge of interest in Multi-Target Cross-Domain Recommendation (MTCDR), which aims to enhance recommendation performance across multiple domains simultane…
Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning
Shanle Zheng, Keqin Bao, Jizhi Zhang +3
LLM-based recommender systems have made significant progress; however, the deployment cost associated with the large parameter volume of LLMs still hinders their real-world applica…
K-order Ranking Preference Optimization for Large Language Models
Shihao Cai, Chongming Gao, Yang Zhang +5
To adapt large language models (LLMs) to ranking tasks, existing list-wise methods, represented by list-wise Direct Preference Optimization (DPO), focus on optimizing partial-order…
Reinforced Latent Reasoning for LLM-based Recommendation
Yang Zhang, Wenxin Xu, Xiaoyan Zhao +4
Large Language Models (LLMs) have demonstrated impressive reasoning capabilities in complex problem-solving tasks, sparking growing interest in their application to preference reas…
DRC: Enhancing Personalized Image Generation via Disentangled Representation Composition
Yiyan Xu, Wuqiang Zheng, Wenjie Wang +5
Personalized image generation has emerged as a promising direction in multimodal content creation. It aims to synthesize images tailored to individual style preferences (e.g., colo…
Measuring What Makes You Unique: Difference-Aware User Modeling for Enhancing LLM Personalization
Yilun Qiu, Xiaoyan Zhao, Yang Zhang +5
Personalizing Large Language Models (LLMs) has become a critical step in facilitating their widespread application to enhance individual life experiences. In pursuit of personaliza…