5 papers
When Relevance Meets Novelty: Dual-Stable Periodic Optimization for Serendipitous Recommendation
Hongxiang Lin, Hao Guo, Zeshun Li +6
Traditional recommendation systems tend to trap users in strong feedback loops by excessively pushing content aligned with their historical preferences, thereby limiting exploratio…
Dynamic Forgetting and Spatio-Temporal Periodic Interest Modeling for Local-Life Service Recommendation
Zhaoyu Hu, Jianyang Wang, Hao Guo +6
In the context of the booming digital economy, recommendation systems, as a key link connecting users and numerous services, face challenges in modeling user behavior sequences on…
Conceptual Design Report of Super Tau-Charm Facility: The Accelerator
Jiancong Bao, Anton Bogomyagkov, Zexin Cao +93
Electron-positron colliders operating in the GeV region of center-of-mass energies or the Tau-Charm energy region, have been proven to enable competitive frontier research, due to…
Action is All You Need: Dual-Flow Generative Ranking Network for Recommendation
Hao Guo, Erpeng Xue, Lei Huang +5
Deep Learning Recommendation Models (DLRMs) often rely on extensive manual feature engineering to improve accuracy and user experience, which increases system complexity and limits…
SessionRec: Next Session Prediction Paradigm For Generative Sequential Recommendation
Lei Huang, Hao Guo, Linzhi Peng +7
We introduce SessionRec, a novel next-session prediction paradigm (NSPP) for generative sequential recommendation, addressing the fundamental misalignment between conventional next…