58 citations · 85 across the 11 of their papers we have counts for
11 papers
FilterLLM: Text-To-Distribution LLM for Billion-Scale Cold-Start Recommendation
Ruochen Liu, Hao Chen, Yuanchen Bei +6
Large Language Model (LLM)-based cold-start recommendation systems continue to face significant computational challenges in billion-scale scenarios, as they follow a "Text-to-Judgm…
When Graph meets Multimodal: Benchmarking and Meditating on Multimodal Attributed Graphs Learning
Hao Yan, Chaozhuo Li, Jun Yin +6
Multimodal Attributed Graphs (MAGs) are ubiquitous in real-world applications, encompassing extensive knowledge through multimodal attributes attached to nodes (e.g., texts and ima…
Lighter And Better: Towards Flexible Context Adaptation For Retrieval Augmented Generation
Zheng Liu, Chenyuan Wu, Ninglu Shao +3
The existing Retrieval-Augmented Generation (RAG) systems face significant challenges in terms of cost and effectiveness. On one hand, they need to encode the lengthy retrieved con…
GPT4Rec: Graph Prompt Tuning for Streaming Recommendation
Peiyan Zhang, Yuchen Yan, Xi Zhang +5
In the realm of personalized recommender systems, the challenge of adapting to evolving user preferences and the continuous influx of new users and items is paramount. Conventional…
High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text-attributed Graphs
Peiyan Zhang, Chaozhuo Li, Liying Kang +4
We investigate node representation learning on text-attributed graphs (TAGs), where nodes are associated with text information. Although recent studies on graph neural networks (GN…
Large Language Model Simulator for Cold-Start Recommendation
Feiran Huang, Yuanchen Bei, Zhenghang Yang +6
Recommending cold items remains a significant challenge in billion-scale online recommendation systems. While warm items benefit from historical user behaviors, cold items rely sol…
Multi-Behavior Collaborative Filtering with Partial Order Graph Convolutional Networks
Yijie Zhang, Yuanchen Bei, Hao Chen +6
Representing information of multiple behaviors in the single graph collaborative filtering (CF) vector has been a long-standing challenge. This is because different behaviors natur…
Macro Graph Neural Networks for Online Billion-Scale Recommender Systems
Hao Chen, Yuanchen Bei, Qijie Shen +6
Predicting Click-Through Rate (CTR) in billion-scale recommender systems poses a long-standing challenge for Graph Neural Networks (GNNs) due to the overwhelming computational comp…
MultiSPANS: A Multi-range Spatial-Temporal Transformer Network for Traffic Forecast via Structural Entropy Optimization
Dongcheng Zou, Senzhang Wang, Xuefeng Li +5
Traffic forecasting is a complex multivariate time-series regression task of paramount importance for traffic management and planning. However, existing approaches often struggle t…
AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation
Juyong Jiang, Peiyan Zhang, Yingtao Luo +6
Sequential recommendation (SR) aims to model users dynamic preferences from a series of interactions. A pivotal challenge in user modeling for SR lies in the inherent variability o…
Improving Sequential Recommendations via Bidirectional Temporal Data Augmentation with Pre-training
Juyong Jiang, Peiyan Zhang, Yingtao Luo +6
Sequential recommendation systems are integral to discerning temporal user preferences. Yet, the task of learning from abbreviated user interaction sequences poses a notable challe…