7 papers
DMESR: Dual-view MLLM-based Enhancing Framework for Multimodal Sequential Recommendation
Mingyao Huang, Qidong Liu, Wenxuan Yang +5
Sequential Recommender Systems (SRS) aim to predict users' next interaction based on their historical behaviors, while still facing the challenge of data sparsity. With the rapid a…
Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendation
Qidong Liu, Xiangyu Zhao, Yejing Wang +6
Cross-domain Sequential Recommendation (CDSR) aims to extract the preference from the user's historical interactions across various domains. Despite some progress in CDSR, two prob…
LLMSeR: Enhancing Sequential Recommendation via LLM-based Data Augmentation
Yuqi Sun, Qidong Liu, Haiping Zhu +1
Sequential Recommender Systems (SRS) have become a cornerstone of online platforms, leveraging users' historical interaction data to forecast their next potential engagement. Despi…
Large Language Model Enhanced Recommender Systems: A Survey
Qidong Liu, Xiangyu Zhao, Yuhao Wang +9
Large Language Model (LLM) has transformative potential in various domains, including recommender systems (RS). There have been a handful of research that focuses on empowering the…
Large Language Model Distilling Medication Recommendation Model
Qidong Liu, Xian Wu, Xiangyu Zhao +4
The recommendation of medication is a vital aspect of intelligent healthcare systems, as it involves prescribing the most suitable drugs based on a patient's specific health needs.…
A Contrastive Pretrain Model with Prompt Tuning for Multi-center Medication Recommendation
Qidong Liu, Zhaopeng Qiu, Xiangyu Zhao +4
Medication recommendation is one of the most critical health-related applications, which has attracted extensive research interest recently. Most existing works focus on a single h…