41 citations · 82 across the 7 of their papers we have counts for
7 papers
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
Yu Cheng, Yunzhu Pan, Jiaqi Zhang +3
Recommender systems (RS) have achieved significant success by leveraging explicit identification (ID) features. However, the full potential of content features, especially the pure…
NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation
Jiaqi Zhang, Yu Cheng, Yongxin Ni +6
Large foundational models, through upstream pre-training and downstream fine-tuning, have achieved immense success in the broad AI community due to improved model performance and s…
Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation
Yunzhu Pan, Chen Gao, Jianxin Chang +5
Sequential recommendation is one of the most important tasks in recommender systems, which aims to recommend the next interacted item with historical behaviors as input. Traditiona…
Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System
Yunzhu Pan, Nian Li, Chen Gao +5
Short-video recommendation is one of the most important recommendation applications in today's industrial information systems. Compared with other recommendation tasks, the enormou…
Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited
Zheng Yuan, Fajie Yuan, Yu Song +5
Recommendation models that utilize unique identities (IDs) to represent distinct users and items have been state-of-the-art (SOTA) and dominated the recommender systems (RS) litera…
Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights
Junchen Fu, Fajie Yuan, Yu Song +6
Adapters, a plug-in neural network module with some tunable parameters, have emerged as a parameter-efficient transfer learning technique for adapting pre-trained models to downstr…
Multi-Dimensional Self Attention based Approach for Remaining Useful Life Estimation
Zhi Lai, Mengjuan Liu, Yunzhu Pan +1
Remaining Useful Life (RUL) estimation plays a critical role in Prognostics and Health Management (PHM). Traditional machine health maintenance systems are often costly, requiring…