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cs.IR2026★ 2 cited
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
Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
Langming Liu, Wanyu Wang, Chi Zhang +6
Online advertising in recommendation platforms has gained significant attention, with a predominant focus on channel recommendation and budget allocation strategies. However, curre…
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…