1 citations · 1 across the 10 of their papers we have counts for
5 papers · 1 filter
A Better Spur Should Start From Each Objective
Shanwen Mao, Hao Zhang, Guangtao nie +4
Real-world Multi-Objective Reinforcement Learning (MORL) often suffers from sparse rewards, reward conflicts, and late-stage reward tug-of-war, causing traditional linear scalariza…
CogRec: Structure-Cognitive Fast-and-Slow Reasoning for Generative Recommendation
Xiang Liu, Jingsong Su, Shuqi Zhao +7
Semantic-ID-based generative recommendation represents each item as a hierarchical discrete token sequence and reformulates next-item prediction as constrained sequence generation.…
HoloRec: Holistic Encoding and Interleaved Reasoning for Generative Recommendation
Shuqi Zhao, Jingsong Su, Xiang Liu +9
Generative recommendation models that formulate the task as sequence generation overcome the objective fragmentation problem of traditional cascade architectures, yet existing appr…
Towards Efficient and Generalizable Retrieval: Adaptive Semantic Quantization and Residual Knowledge Transfer
Huimu Wang, Xingzhi Yao, Yiming Qiu +6
While semantic ID-based generative retrieval enables efficient end-to-end modeling in industrial applications, these methods face a persistent trade-off. On one hand, data-rich hea…
RAD-DPO: Robust Adaptive Denoising Direct Preference Optimization for Generative Retrieval in E-commerce
Zhiguo Chen, Guohao Sun, Yiming Qiu +6
Generative Retrieval (GR) is rapidly transforming e-commerce search by replacing traditional multi-stage pipelines with the autoregressive decoding of structured Semantic IDs (SIDs…