20 citations · 34 across the 6 of their papers we have counts for
5 papers · 1 filter
PRec: Distilling Prior--Posterior Preference Reasoning for LLM-based Recommendation
Jinfei Chen, Weihai Lu, Jiawei Cheng
Large language models (LLMs) exhibit strong semantic understanding and preference reasoning capabilities, offering new opportunities for user modeling in recommender systems. Exist…
AtomRec: Evolving Atomic Memory for Agentic Recommendation
Peiyu Hu, Weihai Lu, Siying Gu +5
Agentic recommender systems use large language models to maintain semantic memory and support evidence-aware recommendation. However, existing memory mechanisms often compress user…
Hierarchical Latent Reasoning for LLM-based Recommendation
Peiyu Hu, Siying Gu, Weihai Lu +8
Large Language Models (LLMs) have shown strong potential for recommendation by leveraging their semantic understanding and contextual modeling capabilities. Recent studies further…
Diffusion-based Multi-modal Synergy Interest Network for Click-through Rate Prediction
Xiaoxi Cui, Weihai Lu, Yu Tong +2
In click-through rate prediction, click-through rate prediction is used to model users' interests. However, most of the existing CTR prediction methods are mainly based on the ID m…
Multi-Modal Multi-Behavior Sequential Recommendation with Conditional Diffusion-Based Feature Denoising
Xiaoxi Cui, Weihai Lu, Yu Tong +2
The sequential recommendation system utilizes historical user interactions to predict preferences. Effectively integrating diverse user behavior patterns with rich multimodal infor…