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- Zhejiang UniversityCN121 papers
- Alibaba Group (United States)US60 papers
- Tsinghua UniversityCN52 papers
- Peking UniversityCN50 papers
- University of Science and Technology of ChinaCN50 papers
- Nanyang Technological UniversitySG42 papers
- Chinese Academy of SciencesCN37 papers
- Shanghai Jiao Tong UniversityCN34 papers
- University of Chinese Academy of SciencesCN26 papers
- University of Electronic Science and Technology of ChinaCN19 papers
- Fudan UniversityCN18 papers
- Hong Kong University of Science and TechnologyHK17 papers
141 papers · 1 filter
TMallGS: Scaling Unified Feature and Sequence Modeling for Generative E-commerce Search
Zhentao Song, Yufeng Gao, Xing Fang +5
In industrial search and ranking systems, Click-Through Rate (CTR) prediction is shifting from traditional Deep Learning Recommendation Models (DLRM) toward unified, compute-intens…
Learning to Forget: Satiation-Aware Long-Sequence Transducers for Mitigating Post-Purchase Redundancy
Yipin Dai, Ruocong Tang, Xing Fang +4
Sequential recommendation models predominantly interpret user interactions as positive signals for preference accumulation. However, in e-commerce scenarios, a purchase action ofte…
Cheaper is Better: A Discount-Aware Network for Conversion Rate Prediction in E-commerce Recommendation System
Ruocong Tang, Yang Huang, Xing Fang +3
Post-click conversion rate (CVR) is a crucial element in online recommendation systems, which addresses significant challenges such as data sparsity (DS), sample selection bias (SS…
DeGRe: Dense-supervised Generative Reranking for Recommendation
Chaotian Song, Jingyao Zhang, Chenghao Chen +6
In multi-stage recommender systems, reranking optimizes overall utility by capturing intra-list contextual dependencies, yet its central challenge lies in exploring optimal sequenc…
Counterfactual Multi-task Learning for Delayed Conversion Modeling in E-commerce Sales Pre-Promotion
Xin Song, Kaiyuan Li, Jinxin Hu
Sales promotions, as short-term incentives to stimulate product purchases, play a pivotal role in modern e-commerce marketing strategies. During promotional events, user behavior p…
RecGPT-Mobile: On-Device Large Language Models for User Intent Understanding in Taobao Feed Recommendation
Bin Zhang, Weipeng Huang, Dimin Wang +9
Predicting a user's next search query from recent interaction behaviors is a critical problem in modern e-commerce systems, particularly in scenarios where user intent evolves rapi…