3 papers
cs.CV2026
Premier: Personalized Preference Modulation with Learnable User Embedding in Text-to-Image Generation
Zihao Wang, Yuxiang Wei, Xinpeng Zhou +5
Text-to-image generation has advanced rapidly, yet it still struggles to capture the nuanced user preferences. Existing approaches typically rely on multimodal large language model…
cs.IR2026
Unlocking Scaling Law in Industrial Recommendation Systems with a Three-step Paradigm based Large User Model
Bencheng Yan, Shilei Liu, Zhiyuan Zeng +10
Recent advancements in autoregressive Large Language Models (LLMs) have achieved significant milestones, largely attributed to their scalability, often referred to as the "scaling…
cs.IR2025
UQABench: Evaluating User Embedding for Prompting LLMs in Personalized Question Answering
Langming Liu, Shilei Liu, Yujin Yuan +10
Large language models (LLMs) achieve remarkable success in natural language processing (NLP). In practical scenarios like recommendations, as users increasingly seek personalized e…