7 papers
Multi-Decoder OneRec: Controllable Generative Retrieval for Multi-Objective Industrial Recommendation
You Wang, Zhao Liu, Guoping Tang +11
Industrial recommender systems build candidate pools by assigning explicit quotas to objective-specific retrieval routes. This design offers quota control but increasingly fragment…
RECAP: Feedback-Driven Streaming Semantic User Profiles for Short-Video Recommendation
Ziyi Zhao, Xiaoyou Zhou, Xiao Lv +13
Language-based user profiles convert long behavioral histories into explicit semantic representations for recommendation. However, most profile generators are optimized in an open…
DADF: A Distribution-Aware Debiasing Framework for Watch-Time Regression in Recommender Systems
Yiqing Yang, Xinlong Zhao, Zhao Liu +4
Watch-time predictors in short-video recommender systems can be approximately calibrated by their own scores while still overestimating short observations and underestimating long…
SARM: LLM-Augmented Semantic Anchor for End-to-End Live-Streaming Ranking
Ruochen Yang, Yueyang Liu, Zijie Zhuang +14
Large-scale live-streaming recommendation requires precise modeling of non-stationary content semantics under strict real-time serving constraints. In industrial deployment, two co…
CAPTS: Channel-Aware, Preference-Aligned Trigger Selection for Multi-Channel Item-to-Item Retrieval
Xiaoyou Zhou, Yuqi Liu, Zhao Liu +4
Large-scale industrial recommender systems commonly adopt multi-channel retrieval for candidate generation, combining direct user-to-item (U2I) retrieval with two-hop user-to-item-…
DiffGRM: Diffusion-based Generative Recommendation Model
Zhao Liu, Yichen Zhu, Yiqing Yang +7
Generative recommendation (GR) is an emerging paradigm that represents each item via a tokenizer as an n-digit semantic ID (SID) and predicts the next item by autoregressively gene…
MARM: Unlocking the Future of Recommendation Systems through Memory Augmentation and Scalable Complexity
Xiao Lv, Jiangxia Cao, Shijie Guan +7
Scaling-law has guided the language model designing for past years, however, it is worth noting that the scaling laws of NLP cannot be directly applied to RecSys due to the followi…