4 citations · 7 across the 16 of their papers we have counts for
10 papers · 1 filter
Deep Situation-Aware Interaction Network for Click-Through Rate Prediction
Yimin Lv, Shuli Wang, Beihong Jin +6
User behavior sequence modeling plays a significant role in Click-Through Rate (CTR) prediction on e-commerce platforms. Except for the interacted items, user behaviors contain ric…
On Negative-aware Preference Optimization for Recommendation
Chenlu Ding, Daoxuan Liu, Jiancan Wu +6
Recommendation systems leverage user interaction data to suggest relevant items while filtering out irrelevant (negative) ones. The rise of large language models (LLMs) has garnere…
EGA-V1: Unifying Online Advertising with End-to-End Learning
Junyan Qiu, Ze Wang, Fan Zhang +7
Modern industrial advertising systems commonly employ Multi-stage Cascading Architectures (MCA) to balance computational efficiency with ranking accuracy. However, this approach pr…
EGA-V2: An End-to-end Generative Framework for Industrial Advertising
Zuowu Zheng, Ze Wang, Fan Yang +4
Traditional online industrial advertising systems suffer from the limitations of multi-stage cascaded architectures, which often discard high-potential candidates prematurely and d…
TBIN: Modeling Long Textual Behavior Data for CTR Prediction
Shuwei Chen, Xiang Li, Jian Dong +3
Click-through rate (CTR) prediction plays a pivotal role in the success of recommendations. Inspired by the recent thriving of language models (LMs), a surge of works improve predi…
Cross-Element Combinatorial Selection for Multi-Element Creative in Display Advertising
Wei Zhang, Ping Zhang, Jian Dong +5
The effectiveness of ad creatives is greatly influenced by their visual appearance. Advertising platforms can generate ad creatives with different appearances by combining creative…
MDDL: A Framework for Reinforcement Learning-based Position Allocation in Multi-Channel Feed
Xiaowen Shi, Ze Wang, Yuanying Cai +6
Nowadays, the mainstream approach in position allocation system is to utilize a reinforcement learning model to allocate appropriate locations for items in various channels and the…
PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce
Xiaowen Shi, Fan Yang, Ze Wang +6
Re-ranking draws increased attention on both academics and industries, which rearranges the ranking list by modeling the mutual influence among items to better meet users' demands.…
Decision-Making Context Interaction Network for Click-Through Rate Prediction
Xiang Li, Shuwei Chen, Jian Dong +4
Click-through rate (CTR) prediction is crucial in recommendation and online advertising systems. Existing methods usually model user behaviors, while ignoring the informative conte…
Hybrid Transfer in Deep Reinforcement Learning for Ads Allocation
Ze Wang, Guogang Liao, Xiaowen Shi +6
Ads allocation, which involves allocating ads and organic items to limited slots in feed with the purpose of maximizing platform revenue, has become a research hotspot. Notice that…