collaborators

6 papers

cs.CL2026

Node-to-Neighborhood Semantic Consistency: Text-Topology Alignment for TAGs Anomaly Detection

Bochen Lin, Jianxiang Yu, Jiayi Wu +3

Graph anomaly detection (GAD) on text-attributed graphs (TAGs) is vital for applications such as fraud detection and academic integrity verification. Existing approaches generally…

cs.IR2026

Dual-Tree LLM-Enhanced Negative Sampling for Implicit Collaborative Filtering

Jiayi Wu, Zhengyu Wu, Xunkai Li +2

Negative sampling is a pivotal technique in implicit collaborative filtering (CF) recommendation, enabling efficient and effective training by contrasting observed interactions wit…

cs.IR2026

TFPS: A Temporal Filtration-enhanced Positive Sample Set Construction Method for Implicit Collaborative Filtering

Jiayi Wu, Zhengyu Wu, Xunkai Li +2

The negative sampling strategy can effectively train collaborative filtering (CF) recommendation models based on implicit feedback by constructing positive and negative samples. Ho…

cs.IR2026

A Topology-Aware Positive Sample Set Construction and Feature Optimization Method in Implicit Collaborative Filtering

Jiayi Wu, Zhengyu Wu, Xunkai Li +2

Negative sampling strategies are widely used in implicit collaborative filtering to address issues like data sparsity and class imbalance. However, these methods often introduce fa…

cs.IR2026

A Simple yet Effective Negative Sampling Plugin for Constructing Positive Sample Pairs in Implicit Collaborative Filtering

Jiayi Wu, Zhengyu Wu, Xunkai Li +2

Most implicit collaborative filtering (CF) models are trained with negative sampling, where existing work designs sophisticated strategies for high-quality negatives while largely…

cs.LG2024

Graph Learning in the Era of LLMs: A Survey from the Perspective of Data, Models, and Tasks

Xunkai Li, Zhengyu Wu, Jiayi Wu +4

With the increasing prevalence of cross-domain Text-Attributed Graph (TAG) Data (e.g., citation networks, recommendation systems, social networks, and ai4science), the integration…