24 citations · 47 across the 18 of their papers we have counts for
5 papers · 1 filter
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…
LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation
Qidong Liu, Xian Wu, Wanyu Wang +5
Sequential Recommender Systems (SRS), which model a user's interaction history to predict the next item of interest, are widely used in various applications. However, existing SRS…
AutoPal: Autonomous Adaptation to Users for Personal AI Companionship
Yi Cheng, Wenge Liu, Kaishuai Xu +6
Previous research has demonstrated the potential of AI agents to act as companions that can provide constant emotional support for humans. In this paper, we emphasize the necessity…
LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation
Qidong Liu, Xian Wu, Yejing Wang +4
Sequential recommender systems (SRS) aim to predict users' subsequent choices based on their historical interactions and have found applications in diverse fields such as e-commerc…
Multi-perspective Improvement of Knowledge Graph Completion with Large Language Models
Derong Xu, Ziheng Zhang, Zhenxi Lin +6
Knowledge graph completion (KGC) is a widely used method to tackle incompleteness in knowledge graphs (KGs) by making predictions for missing links. Description-based KGC leverages…