28 citations · 150 across the 50 of their papers we have counts for
9 papers · 1 filter
Multi-Modality is All You Need for Transferable Recommender Systems
Youhua Li, Hanwen Du, Yongxin Ni +4
ID-based Recommender Systems (RecSys), where each item is assigned a unique identifier and subsequently converted into an embedding vector, have dominated the designing of RecSys.…
Scene-Driven Multimodal Knowledge Graph Construction for Embodied AI
Song Yaoxian, Sun Penglei, Liu Haoyu +4
Embodied AI is one of the most popular studies in artificial intelligence and robotics, which can effectively improve the intelligence of real-world agents (i.e. robots) serving hu…
Meta-optimized Joint Generative and Contrastive Learning for Sequential Recommendation
Yongjing Hao, Pengpeng Zhao, Junhua Fang +5
Sequential Recommendation (SR) has received increasing attention due to its ability to capture user dynamic preferences. Recently, Contrastive Learning (CL) provides an effective a…
A Universal Scheme for Dynamic Partitioned Shortest Path Index: Survey, Improvement, and Experiments
Mengxuan Zhang, Xinjie Zhou, Lei Li +4
Shortest Path (SP) computation is a fundamental operation in many real-life applications such as navigation on road networks, link analysis on social networks, etc. These networks…
Invariant representation learning for sequential recommendation
Xiaofan Zhou
Sequential recommendation involves automatically recommending the next item to users based on their historical item sequence. While most prior research employs RNN or transformer m…
Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks
Zhili Wang, Shimin Di, Lei Chen +1
Recently, graph neural networks (GNNs) have shown its unprecedented success in many graph-related tasks. However, GNNs face the label scarcity issue as other neural networks do. Th…
HeteFedRec: Federated Recommender Systems with Model Heterogeneity
Wei Yuan, Liang Qu, Lizhen Cui +3
Owing to the nature of privacy protection, federated recommender systems (FedRecs) have garnered increasing interest in the realm of on-device recommender systems. However, most ex…
Contrastive Enhanced Slide Filter Mixer for Sequential Recommendation
Xinyu Du, Huanhuan Yuan, Pengpeng Zhao +5
Sequential recommendation (SR) aims to model user preferences by capturing behavior patterns from their item historical interaction data. Most existing methods model user preferenc…
Sequential Recommendation with Diffusion Models
Hanwen Du, Huanhuan Yuan, Zhen Huang +2
Generative models, such as Variational Auto-Encoder (VAE) and Generative Adversarial Network (GAN), have been successfully applied in sequential recommendation. These methods requi…