From the 3 of 23 papers with an AI index.
9 citations
- Shanghai Jiao Tong UniversityCN3 papers
- Zhejiang UniversityCN2 papers
- Beihang UniversityCN1 paper
- China Electronics Technology Group CorporationCN1 paper
- Chinese Academy of SciencesCN1 paper
- Cloud Computing CenterCN1 paper
- East China University of Science and TechnologyCN1 paper
- Fudan UniversityCN1 paper
- Fuzhou UniversityCN1 paper
- Hong Kong Footwear FederationCN1 paper
- Horizon Robotics (China)1 paper
- Huazhong University of Science and TechnologyCN1 paper
8 papers · 1 filter
TMallGS: Scaling Unified Feature and Sequence Modeling for Generative E-commerce Search
Zhentao Song, Yufeng Gao, Xing Fang +5
The paper introduces TMallGS, a transformer-based ranking architecture for e‑commerce search that combines specialized tokenization, field‑adaptive transformers, and bias‑aware tra…
Learning to Forget: Satiation-Aware Long-Sequence Transducers for Mitigating Post-Purchase Redundancy
Yipin Dai, Ruocong Tang, Xing Fang +4
The paper introduces a satiation-aware framework for sequential recommendation that detects when a purchase satisfies a user’s intent and temporarily suppresses related items, then…
Cheaper is Better: A Discount-Aware Network for Conversion Rate Prediction in E-commerce Recommendation System
Ruocong Tang, Yang Huang, Xing Fang +3
The paper introduces a Discount-Aware Network (DANet) that incorporates item discount information via Fourier-based time‑frequency analysis and bias‑mitigation modules to improve p…
TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance
Jianhui Yang, Yiming Jin, Pengkun Jiao +6
Query-product relevance prediction is fundamental to e-commerce search and has become even more critical in the era of AI-powered shopping, where semantic understanding and complex…
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…