Multi-Interactive Attention Network for Fine-grained Feature Learning in
CTR Prediction

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Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction

13 December 2020

Kai Zhang

Qi Liu

Enhong Chen

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Papers citing "Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction"

8 / 8 papers shown

Title
AdaF^2M^2: Comprehensive Learning and Responsive Leveraging Features in Recommendation System Yongchun Zhu Jingwu Chen Ling Chen Yongqian Li Feng Zhang Xiao Yang Zuotao Liu 88 0 0 28 Jan 2025
PPM : A Pre-trained Plug-in Model for Click-through Rate Prediction Yuanbo Gao Peng Lin Dongyue Wang Feng Mei Xiwei Zhao Sulong Xu Jinghe Hu LRM 47 0 0 15 Mar 2024
AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking Yang Yu Qi Liu Kai Zhang Yuren Zhang Chao Song Min Hou Yuqing Yuan Zhihao Ye Zaixin Zhang Sanshi Lei Yu 66 2 0 15 Oct 2023
FeatureBox: Feature Engineering on GPUs for Massive-Scale Ads Systems Weijie Zhao Xuewu Jiao Xinsheng Luo Jingxue Li Belhal Karimi Ping Li 70 2 0 26 Sep 2022
Triangle Graph Interest Network for Click-through Rate Prediction Wensen Jiang Yizhu Jiao Qingqin Wang Chuanming Liang Lijie Guo Yao Zhang Zhijun Sun Yun Xiong Yangyong Zhu 39 18 0 06 Feb 2022
Deep Interest Highlight Network for Click-Through Rate Prediction in Trigger-Induced Recommendation Qi Shen Hong Wen Wanjie Tao Jing Zhang Fuyu Lv Zulong Chen Zhao Li 62 47 0 05 Feb 2022
SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation Kai Zhang Hao Qian Qi Liu Qing Cui Jun Zhou Jianhui Ma Enhong Chen 47 13 0 18 Aug 2021
FINT: Field-aware INTeraction Neural Network For CTR Prediction Zhishan Zhao Sen Yang Guohui Liu Dawei Feng Ke Xu 50 9 0 05 Jul 2021