4 papers
TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendation
Haohao Qu, Wenqi Fan, Zihuai Zhao +1
There is a growing interest in utilizing large-scale language models (LLMs) to advance next-generation Recommender Systems (RecSys), driven by their outstanding language understand…
Dataset Condensation for Recommendation
Jiahao Wu, Wenqi Fan, Jingfan Chen +5
Training recommendation models on large datasets requires significant time and resources. It is desired to construct concise yet informative datasets for efficient training. Recent…
Backdoor Graph Condensation
Jiahao Wu, Ning Lu, Zeiyu Dai +5
Graph condensation has recently emerged as a prevalent technique to improve the training efficiency for graph neural networks (GNNs). It condenses a large graph into a small one su…
TF-DCon: Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation
Jiahao Wu, Qijiong Liu, Hengchang Hu +5
Modern techniques in Content-based Recommendation (CBR) leverage item content information to provide personalized services to users, but suffer from resource-intensive training on…