5 citations · 6 across the 12 of their papers we have counts for
7 papers · 1 filter
Watermarking Large Language Model-based Time Series Forecasting
Wei Yuan, Chaoqun Yang, Yu Xing +3
Large Language Model-based Time Series Forecasting (LLMTS) has shown remarkable promise in handling complex and diverse temporal data, representing a significant step toward founda…
On Mitigating Data Sparsity in Conversational Recommender Systems
Sixiao Zhang, Mingrui Liu, Wei Yuan +2
Conversational recommender systems (CRSs) infer user preferences from dialogue contexts, but they suffer from severe data sparsity in both dialogue and entity spaces. Dialogue data…
HMamba: Hyperbolic Mamba for Sequential Recommendation
Qianru Zhang, Honggang Wen, Wei Yuan +4
Sequential recommendation systems have become a cornerstone of personalized services, adept at modeling the temporal evolution of user preferences by capturing dynamic interaction…
M2Rec: Multi-scale Mamba for Efficient Sequential Recommendation
Qianru Zhang, Liang Qu, Honggang Wen +4
Sequential recommendation systems aim to predict users' next preferences based on their interaction histories, but existing approaches face critical limitations in efficiency and m…
Multi-agents based User Values Mining for Recommendation
Lijian Chen, Wei Yuan, Tong Chen +3
Recommender systems have rapidly evolved and become integral to many online services. However, existing systems sometimes produce unstable and unsatisfactory recommendations that f…
Data Watermarking for Sequential Recommender Systems
Sixiao Zhang, Cheng Long, Wei Yuan +2
In the era of large foundation models, data has become a crucial component in building high-performance AI systems. As the demand for high-quality and large-scale data continues to…
Watermarking Recommender Systems
Sixiao Zhang, Cheng Long, Wei Yuan +2
Recommender systems embody significant commercial value and represent crucial intellectual property. However, the integrity of these systems is constantly challenged by malicious a…