38 citations · 61 across the 5 of their papers we have counts for
5 papers
Large Language Model driven Policy Exploration for Recommender Systems
Jie Wang, Alexandros Karatzoglou, Ioannis Arapakis +1
Recent advancements in Recommender Systems (RS) have incorporated Reinforcement Learning (RL), framing the recommendation as a Markov Decision Process (MDP). However, offline RL po…
Hire: Hybrid-modal Interaction with Multiple Relational Enhancements for Image-Text Matching
Xuri Ge, Fuhai Chen, Songpei Xu +3
Image-text matching (ITM) is a fundamental problem in computer vision. The key issue lies in jointly learning the visual and textual representation to estimate their similarity acc…
3SHNet: Boosting Image-Sentence Retrieval via Visual Semantic-Spatial Self-Highlighting
Xuri Ge, Songpei Xu, Fuhai Chen +4
In this paper, we propose a novel visual Semantic-Spatial Self-Highlighting Network (termed 3SHNet) for high-precision, high-efficiency and high-generalization image-sentence retri…
IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT
Junchen Fu, Xuri Ge, Xin Xin +4
Multimodal foundation models are transformative in sequential recommender systems, leveraging powerful representation learning capabilities. While Parameter-efficient Fine-tuning (…
Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling
Jie Wang, Alexandros Karatzoglou, Ioannis Arapakis +1
Reinforcement Learning (RL)-based recommender systems have demonstrated promising performance in meeting user expectations by learning to make accurate next-item recommendations fr…