Negative Exclusion Filtering: Optimizing Ad Delivery Efficiency for Large-Scale Social Media Platforms - Min Zhang; Ganlin Song; Fang Zhou; Dong Liang; Jianwei Xiao; Shengyu Huang; Lizhang Qin; Xi Yan; Rong Shi; Xiyuan Chen; Jing Xu; Zhaojun Zhang; et al. (Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025, Padua, Italy, July 13-18, 2025, 2025)

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation - Mingfu Liang; Xi Liu; Rong Jin; Boyang Liu; Qiuling Suo; Qinghai Zhou; Song Zhou; Laming Chen; Hua Zheng; Zhiyuan Li; Shali Jiang; Jiyan Yang; et al. (Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, Sydney, NSW, Australia, 28 April 2025 - 2 May 2025, 2025)

Personalized Interpolation: An Efficient Method to Tame Flexible Optimization Window Estimation - Xin Zhang; Weiliang Li; Rui Li; Zihang Fu; Tongyi Tang; Zhengyu Zhang; Wen-Yen Chen; Nima Noorshams; Nirav Jasapara; Xiaowen Ding; Ellie Wen; Xue Feng (CoRR, 2025)

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation - Mingfu Liang; Xi Liu; Rong Jin; Boyang Liu; Qiuling Suo; Qinghai Zhou; Song Zhou; Laming Chen; Hua Zheng; Zhiyuan Li; Shali Jiang; Jiyan Yang; et al. (CoRR, 2025)

Wukong: Towards a Scaling Law for Large-Scale Recommendation - Buyun Zhang; Liang Luo; Yuxin Chen; Jade Nie; Xi Liu; Shen Li; Yanli Zhao; Yuchen Hao; Yantao Yao; Ellie Dingqiao Wen; Jongsoo Park; Maxim Naumov; et al. (Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024, 2024)

Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large Scale Recommendation - Liang Luo; Buyun Zhang; Michael Tsang; Yinbin Ma; Ching-Hsiang Chu; Yuxin Chen; Shen Li; Yuchen Hao; Yanli Zhao; Guna Lakshminarayanan; Ellie Wen; Jongsoo Park; et al. (Proceedings of the Seventh Annual Conference on Machine Learning and Systems, MLSys 2024, Santa Clara, CA, USA, May 13-16, 2024, 2024)

QuickUpdate: a Real-Time Personalization System for Large-Scale Recommendation Models - Kiran Kumar Matam; Hani Ramezani; Fan Wang; Zeliang Chen; Yue Dong; Maomao Ding; Zhiwei Zhao; Zhengyu Zhang; Ellie Wen; Assaf Eisenman (21st USENIX Symposium on Networked Systems Design and Implementation, NSDI 2024, Santa Clara, CA, April 15-17, 2024, 2024)

Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation - Liang Luo; Buyun Zhang; Michael Tsang; Yinbin Ma; Ching-Hsiang Chu; Yuxin Chen; Shen Li; Yuchen Hao; Yanli Zhao; Guna Lakshminarayanan; Ellie Dingqiao Wen; Jongsoo Park; et al. (CoRR, 2024)

Wukong: Towards a Scaling Law for Large-Scale Recommendation - Buyun Zhang; Liang Luo; Yuxin Chen; Jade Nie; Xi Liu; Daifeng Guo; Yanli Zhao; Shen Li; Yuchen Hao; Yantao Yao; Guna Lakshminarayanan; Ellie Dingqiao Wen; et al. (CoRR, 2024)

Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking - Xuewei Wang; Qiang Jin; Shengyu Huang; Min Zhang; Xi Liu; Zhengli Zhao; Yukun Chen; Zhengyu Zhang; Jiyan Yang; Ellie Wen; Sagar Chordia; Wenlin Chen; et al. (Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), Long Beach, CA, USA, August 7, 2023, 2023)

AdaEmbed: Adaptive Embedding for Large-Scale Recommendation Models - Fan Lai; Wei Zhang; Rui Liu; William Tsai; Xiaohan Wei; Yuxi Hu; Sabin Devkota; Jianyu Huang; Jongsoo Park; Xing Liu; Zeliang Chen; Ellie Wen; et al. (17th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2023, Boston, MA, USA, July 10-12, 2023, 2023)

Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking - Xuewei Wang; Qiang Jin; Shengyu Huang; Min Zhang; Xi Liu; Zhengli Zhao; Yukun Chen; Zhengyu Zhang; Jiyan Yang; Ellie Wen; Sagar Chordia; Wenlin Chen; et al. (CoRR, 2023)

Software-hardware co-design for fast and scalable training of deep learning recommendation models - Dheevatsa Mudigere; Yuchen Hao; Jianyu Huang; Zhihao Jia; Andrew Tulloch; Srinivas Sridharan; Xing Liu; Mustafa Ozdal; Jade Nie; Jongsoo Park; Liang Luo; Jie Amy Yang; et al. (ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18 - 22, 2022, 2022)

DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction - Buyun Zhang; Liang Luo; Xi Liu; Jay Li; Zeliang Chen; Weilin Zhang; Xiaohan Wei; Yuchen Hao; Michael Tsang; Wenjun Wang; Yang Liu; Huayu Li; et al. (CoRR, 2022)

Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale - Zhaoxia Deng; Jongsoo Park; Ping Tak Peter Tang; Haixin Liu; Jie Yang; Hector Yuen; Jianyu Huang; Daya Shanker Khudia; Xiaohan Wei; Ellie Wen; Dhruv Choudhary; Raghuraman Krishnamoorthi; et al. (IEEE Micro, 2021)

High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models - Dheevatsa Mudigere; Yuchen Hao; Jianyu Huang; Andrew Tulloch; Srinivas Sridharan; Xing Liu; Mustafa Ozdal; Jade Nie; Jongsoo Park; Liang Luo; Jie Amy Yang; Leon Gao; et al. (CoRR, 2021)

Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale - Zhaoxia Deng; Jongsoo Park; Ping Tak Peter Tang; Haixin Liu; Jie Yang; Hector Yuen; Jianyu Huang; Daya Shanker Khudia; Xiaohan Wei; Ellie Wen; Dhruv Choudhary; Raghuraman Krishnamoorthi; et al. (CoRR, 2021)

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data - Mao Ye; Dhruv Choudhary; Jiecao Yu; Ellie Wen; Zeliang Chen; Jiyan Yang; Jongsoo Park; Qiang Liu; Arun Kejariwal (CoRR, 2020)