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20232026
most citedA Comprehensive Survey on Imbalanced Data Learning

16 citations · 42 across the 25 of their papers we have counts for

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5 papers · 1 filter

cs.IR2026

Personalized Communication Skills for Agentic Recommender Systems

Zongwei Wang, Min Gao, Guangyu Hu +2

Agentic recommender systems increasingly employ large language model-based UserAgents to evaluate candidate items through simulated feedback before recommendations are delivered. H…

cs.IR2026

FOSTER: First-order Dataset Distillation for Text-based Sequential Recommendation

Hung Vinh Tran, Tong Chen, Xinyi Gao +3

Text-based sequential recommender systems, while greatly improving recommendation accuracy by incorporating item contexts, are undeniably more expensive to train. By condensing a l…

cs.IR2026

Evolutionary Router Feature Generation for Zero-Shot Graph Anomaly Detection with Mixture-of-Experts

Haiyang Jiang, Tong Chen, Xinyi Gao +3

Zero-shot graph anomaly detection (GAD) has attracted increasing attention recent years, yet the heterogeneity of graph structures, features, and anomaly patterns across graphs mak…

cs.IR2024

ID-Free Not Risk-Free: LLM-Powered Agents Unveil Risks in ID-Free Recommender Systems

Zongwei Wang, Min Gao, Junliang Yu +4

Recent advances in ID-free recommender systems have attracted significant attention for effectively addressing the cold start problem. However, their vulnerability to malicious att…

cs.IR2024★ 1 cited

Challenging Low Homophily in Social Recommendation

Wei Jiang, Xinyi Gao, Guandong Xu +2

Social relations are leveraged to tackle the sparsity issue of user-item interaction data in recommendation under the assumption of social homophily. However, social recommendation…