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2011.05625
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CAN: Feature Co-Action for Click-Through Rate Prediction
11 November 2020
Weijie Bian
Kailun Wu
Lejian Ren
Qi Pi
Yujing Zhang
Can Xiao
Xiang-Rong Sheng
Yong-Nan Zhu
Zhangming Chan
Na Mou
Xinchen Luo
Shiming Xiang
Guorui Zhou
Xiaoqiang Zhu
Hongbo Deng
Re-assign community
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Papers citing
"CAN: Feature Co-Action for Click-Through Rate Prediction"
6 / 6 papers shown
Title
MoE-MLoRA for Multi-Domain CTR Prediction: Efficient Adaptation with Expert Specialization
Ken Yaggel
Eyal German
Aviel Ben Siman Tov
MoE
32
0
0
09 Jun 2025
Measure Domain's Gap: A Similar Domain Selection Principle for Multi-Domain Recommendation
Yi Wen
Yue Liu
Derong Xu
Huishi Luo
Pengyue Jia
...
K. Liang
Maolin Wang
Yiqi Wang
Fuzhen Zhuang
Xiangyu Zhao
45
0
0
26 May 2025
Balancing Efficiency and Effectiveness: An LLM-Infused Approach for Optimized CTR Prediction
Guoxiao Zhang
Yi Wei
Yadong Zhang
Huajian Feng
Qiang Liu
125
1
0
09 Dec 2024
An Adaptive Framework of Geographical Group-Specific Network on O2O Recommendation
Luo Ji
Jiayu Mao
Hailong Shi
Qian Li
Yunfei Chu
Hongxia Yang
18
0
0
28 Dec 2023
Fragment and Integrate Network (FIN): A Novel Spatial-Temporal Modeling Based on Long Sequential Behavior for Online Food Ordering Click-Through Rate Prediction
Jun Li
Jingjian Wang
Hongwei Wang
Xing Deng
Jielong Chen
...
Zekun Wang
Guanjie Xu
Geng Zhang
Feng Shi
Hualei Liu
AI4TS
25
2
0
30 Aug 2023
KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Plugging
Yujing Zhang
Zhangming Chan
Shuhao Xu
Weijie Bian
Shuguang Han
Hongbo Deng
Bo Zheng
108
22
0
22 Aug 2022
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