Title
External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation Mingfu Liang Xi Liu Rong Jin B. Liu Qiuling Suo ... Bo Long Wenlin Chen Rocky Liu Santanu Kolay H. Li 41 1 0 20 Feb 2025
Beyond Self-Consistency: Loss-Balanced Perturbation-Based Regularization Improves Industrial-Scale Ads Ranking Ilqar Ramazanli Hamid Eghbalzadeh Xiaoyi Liu Yang Wang Jiaxiang Fu Kaushik Rangadurai Sem Park Bo Long Xue Feng 44 0 0 05 Feb 2025
360Brew: A Decoder-only Foundation Model for Personalized Ranking and Recommendation Hamed Firooz Maziar Sanjabi Adrian Englhardt Aman Gupta Ben Levine ... Xiaoling Zhai Ya Xu Yu Wang Yun Dai Yun Dai ALM 42 3 0 27 Jan 2025
Data Efficiency for Large Recommendation Models Kshitij Jain Jingru Xie Kevin Regan Cheng Chen Jie Han ... Todd Phillips Myles Sussman Matt Troup Angel Yu Jia Zhuo OffRL 21 0 0 08 Oct 2024
A New Perspective on Shampoo's Preconditioner Depen Morwani Itai Shapira Nikhil Vyas Eran Malach Sham Kakade Lucas Janson 27 7 0 25 Jun 2024
Unified Low-rank Compression Framework for Click-through Rate Prediction Hao Yu Minghao Fu Jiandong Ding Yusheng Zhou Jianxin Wu 22 0 0 28 May 2024
LiRank: Industrial Large Scale Ranking Models at LinkedIn Fedor Borisyuk Mingzhou Zhou Qingquan Song Siyu Zhu B. Tiwana ... Chen-Chen Jiang Haichao Wei Maneesh Varshney Amol Ghoting Souvik Ghosh 24 1 0 10 Feb 2024
PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses Adel Javanmard Matthew Fahrbach Vahab Mirrokni 18 3 0 07 Feb 2024
Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale Wei Wen Kuang-Hung Liu Igor Fedorov Xin Zhang Hang Yin ... Fangqiu Han Jiyan Yang Yuchen Hao Liang Xiong Wen-Yen Chen 23 2 0 14 Nov 2023
What do larger image classifiers memorise? Michal Lukasik Vaishnavh Nagarajan A. S. Rawat A. Menon Sanjiv Kumar 30 5 0 09 Oct 2023
MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems Samuel Hsia Alicia Golden Bilge Acun Newsha Ardalani Zach DeVito Gu-Yeon Wei David Brooks Carole-Jean Wu MoE 38 9 0 04 Oct 2023
A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale Hao-Jun Michael Shi Tsung-Hsien Lee Shintaro Iwasaki Jose Gallego-Posada Zhijing Li Kaushik Rangadurai Dheevatsa Mudigere Michael Rabbat ODL 17 20 0 12 Sep 2023
Unleash the Power of Context: Enhancing Large-Scale Recommender Systems with Context-Based Prediction Models Jan Hartman Assaf Klein Davorin Kopic Natalia Silberstein LRM 14 0 0 25 Jul 2023
Rec4Ad: A Free Lunch to Mitigate Sample Selection Bias for Ads CTR Prediction in Taobao Jingyue Gao Shuguang Han Han Zhu Siran Yang Yuning Jiang Jian Xu Bo Zheng 33 11 0 06 Jun 2023
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions Boxiang Lyu Zhe Feng Zachary Robertson Sanmi Koyejo 15 2 0 01 Jun 2023
KrADagrad: Kronecker Approximation-Domination Gradient Preconditioned Stochastic Optimization Jonathan Mei Alexander Moreno Luke Walters ODL 19 1 0 30 May 2023
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems Benjamin Coleman Wang-Cheng Kang Matthew Fahrbach Ruoxi Wang Lichan Hong Ed H. Chi D. Cheng 25 10 0 20 May 2023
TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings N. Jouppi George Kurian Sheng R. Li Peter C. Ma R. Nagarajan ... Brian Towles C. Young Xiaoping Zhou Zongwei Zhou David A. Patterson BDL VLM 36 336 0 04 Apr 2023
Learning Rate Schedules in the Presence of Distribution Shift Matthew Fahrbach Adel Javanmard Vahab Mirrokni Pratik Worah 19 6 0 27 Mar 2023
Reasonable Scale Machine Learning with Open-Source Metaflow Jacopo Tagliabue Hugo Bowne-Anderson Ville Tuulos Savin Goyal R. Cledat David Berg AIFin AI4CE 14 6 0 21 Mar 2023
TwERC: High Performance Ensembled Candidate Generation for Ads Recommendation at Twitter Vanessa Cai Pradeep Prabakar Manuel Serrano Rebuelta Lucas Rosen Federico Monti ... Tomo Lazovich J. Raj Y. Shrinivasan Hao Li Thomas Markovich 19 0 0 27 Feb 2023
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation Samuel Hsia Udit Gupta Bilge Acun Newsha Ardalani Pan Zhong Gu-Yeon Wei David Brooks Carole-Jean Wu 33 17 0 21 Feb 2023
Improving Training Stability for Multitask Ranking Models in Recommender Systems Jiaxi Tang Yoel Drori Daryl Chang M. Sathiamoorthy Justin Gilmer Li Wei Xinyang Yi Lichan Hong Ed H. Chi 17 10 0 17 Feb 2023
Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions Vladimir Feinberg Xinyi Chen Y. Jennifer Sun Rohan Anil Elad Hazan 21 12 0 07 Feb 2023
FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models Geet Sethi Pallab Bhattacharya Dhruv Choudhary Carole-Jean Wu Christos Kozyrakis 11 5 0 08 Jan 2023
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure Mark Zhao Dhruv Choudhary Devashish Tyagi A. Somani Max Kaplan ... Jongsoo Park Aarti Basant Niket Agarwal Carole-Jean Wu Christos Kozyrakis VLM 18 6 0 09 Nov 2022
Anti-Distillation: Improving reproducibility of deep networks G. Shamir Lorenzo Coviello 34 20 0 19 Oct 2020
Large scale distributed neural network training through online distillation Rohan Anil Gabriel Pereyra Alexandre Passos Róbert Ormándi George E. Dahl Geoffrey E. Hinton FedML 267 404 0 09 Apr 2018