5 citations · 5 across the 5 of their papers we have counts for
6 papers
KUAISHOU Explorer LLM-Rec Challenge 2026: Reasoning Generative Recommendation
Jiangxia Cao, Hao Peng, Wenlong Xu +97
Generative recommendation, has been attracted a surge of attentions in industrial and academic research community, towards to build more smart system to build next-generation recom…
STAR: Structured Tokenization and Target-Aware Interest Representation for PCVR Prediction
Yimeng Xu, Ruihao Zhang, Yingqi Song +2
Post-click conversion rate (PCVR) prediction is a core ranking task in industrial recommender systems. Modern ranking models must jointly capture heterogeneous non-sequential featu…
Taipan: A Query-free Transfer-based Multiple Sensitive Attribute Inference Attack Solely from Auxiliary Graphs
Ying Song, Balaji Palanisamy
Graph-structured data underpin a wide spectrum of modern applications, yet their multiple sensitive attributes are not isolated but deeply coupled with graph topology. This couplin…
GraphToxin: Reconstructing Full Unlearned Graphs from Graph Unlearning
Ying Song, Balaji Palanisamy
Graph unlearning (GU) has emerged as a promising solution to comply with "the right to be forgotten" regulations by enabling the removal of sensitive information upon request. Howe…
Krait: A Backdoor Attack Against Graph Prompt Tuning
Ying Song, Rita Singh, Balaji Palanisamy
Graph prompt tuning has emerged as a promising paradigm to effectively transfer general graph knowledge from pre-trained models to various downstream tasks, particularly in few-sho…
MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage
Ying Song, Balaji Palanisamy
Despite remarkable success in diverse web-based applications, Graph Neural Networks(GNNs) inherit and further exacerbate historical discrimination and social stereotypes, which cri…