15 citations · 17 across the 7 of their papers we have counts for
8 papers · 1 filter
MLLMRec-R1: Incentivizing Reasoning Capability in Large Language Models for Multimodal Sequential Recommendation
Yu Wang, Yonghui Yang, Le Wu +3
Group relative policy optimization (GRPO) has become a standard post-training paradigm for improving reasoning and preference alignment in large language models (LLMs), and has rec…
MealRec: Multi-granularity Sequential Modeling via Hierarchical Diffusion Models for Micro-Video Recommendation
Xinxin Dong, Haokai Ma, Yuze Zheng +3
Micro-video recommendation aims to capture user preferences from the collaborative and context information of the interacted micro-videos, thereby predicting the appropriate videos…
CLEAR: Null-Space Projection for Cross-Modal De-Redundancy in Multimodal Recommendation
Hao Zhan, Yihui Wang, Yonghui Yang +6
Multimodal recommendation has emerged as an effective paradigm for enhancing collaborative filtering by incorporating heterogeneous content modalities. Existing multimodal recommen…
Multimodal Large Language Models with Adaptive Preference Optimization for Sequential Recommendation
Yu Wang, Yonghui Yang, Le Wu +3
Recent advances in Large Language Models (LLMs) have opened new avenues for sequential recommendation by enabling natural language reasoning over user behavior sequences. A common…
Invariance Matters: Empowering Social Recommendation via Graph Invariant Learning
Yonghui Yang, Le Wu, Yuxin Liao +4
Graph-based social recommendation systems have shown significant promise in enhancing recommendation performance, particularly in addressing the issue of data sparsity in user beha…
Joint Item Recommendation and Attribute Inference: An Adaptive Graph Convolutional Network Approach
Le Wu, Yonghui Yang, Kun Zhang +3
In many recommender systems, users and items are associated with attributes, and users show preferences to items. The attribute information describes users'(items') characteristics…