6 papers
Trust-free Personalized Decentralized Learning
Yawen Li, Yan Li, Junping Du +3
Personalized collaborative learning in federated settings faces a critical trade-off between customization and participant trust. Existing approaches typically rely on centralized…
ELMM: Efficient Lightweight Multimodal Large Language Models for Multimodal Knowledge Graph Completion
Wei Huang, Peining Li, Meiyu Liang +7
Multimodal Knowledge Graphs (MKGs) extend traditional knowledge graphs by incorporating visual and textual modalities, enabling richer and more expressive entity representations. H…
Thought-Augmented Planning for LLM-Powered Interactive Recommender Agent
Haocheng Yu, Yaxiong Wu, Hao Wang +6
Interactive recommendation is a typical information-seeking task that allows users to interactively express their needs through natural language and obtain personalized recommendat…
GraphLAMA: Enabling Efficient Adaptation of Graph Language Models with Limited Annotations
Junze Chen, Cheng Yang, Shujie Li +4
Large language models (LLMs) have demonstrated their strong capabilities in various domains, and have been recently integrated for graph analysis as graph language models (GLMs). W…
DiffusionCom: Structure-Aware Multimodal Diffusion Model for Multimodal Knowledge Graph Completion
Wei Huang, Meiyu Liang, Peining Li +5
Most current MKGC approaches are predominantly based on discriminative models that maximize conditional likelihood. These approaches struggle to efficiently capture the complex con…
TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation
Jiaqing Zhang, Mingjia Yin, Hao Wang +5
In the era of data-centric AI, the focus of recommender systems has shifted from model-centric innovations to data-centric approaches. The success of modern AI models is built on l…