Cover Image

Wukong: Towards a Scaling Law for Large-Scale Recommendation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Buyun, Luo, Liang, Chen, Yuxin, Nie, Jade, Liu, Xi, Guo, Daifeng, Zhao, Yanli, Li, Shen, Hao, Yuchen, Yao, Yantao, Lakshminarayanan, Guna, Wen, Ellie Dingqiao, Park, Jongsoo, Naumov, Maxim, Chen, Wenlin
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation
by: Luo, Liang, et al.
Published: (2024)

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale
by: Luo, Liang, et al.
Published: (2026)

Meta Lattice: Model Space Redesign for Cost-Effective Industry-Scale Ads Recommendations
by: Luo, Liang, et al.
Published: (2025)

Implicit Turn-Wise Policy Optimization for Proactive User-LLM Interaction
by: Wang, Haoyu, et al.
Published: (2026)

Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design
by: Hou, Bojian, et al.
Published: (2026)

Climber: Toward Efficient Scaling Laws for Large Recommendation Models
by: Xu, Songpei, et al.
Published: (2025)

Optimizing Sequential Recommendation Models with Scaling Laws and Approximate Entropy
by: Shen, Tingjia, et al.
Published: (2024)

Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures
by: T, Akash Guna R., et al.
Published: (2024)

Towards Neural Scaling Laws on Graphs
by: Liu, Jingzhe, et al.
Published: (2024)

Bending the Scaling Law Curve in Large-Scale Recommendation Systems
by: Ding, Qin, et al.
Published: (2026)

Scaling Laws Revisited: Modeling the Role of Data Quality in Language Model Pretraining
by: Subramanyam, Anirudh, et al.
Published: (2025)

VoiceWukong: Benchmarking Deepfake Voice Detection
by: Yan, Ziwei, et al.
Published: (2024)

Toward highly sensitive, selective, and stable palladium‐based MEMS gas sensors for hydrogen energy security
by: Yuxin Zhao, et al.
Published: (2024)

Assamese poetry by Guna Moran
by: Guna Moran
Published: (2019)

RankMixer: Scaling Up Ranking Models in Industrial Recommenders
by: Zhu, Jie, et al.
Published: (2025)

Amplitude Higgs mode in superconductors with magnetic impurities
by: Li, Yantao, et al.
Published: (2023)

Collective modes in terahertz field response of superconductors with paramagnetic impurities
by: Li, Yantao, et al.
Published: (2024)

Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs
by: Bian, Song, et al.
Published: (2025)

Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendations
by: Wu, Xuansheng, et al.
Published: (2023)

LLaTTE: Scaling Laws for Multi-Stage Sequence Modeling in Large-Scale Ads Recommendation
by: Xiong, Lee, et al.
Published: (2026)

UniMixer: A Unified Architecture for Scaling Laws in Recommendation Systems
by: Ha, Mingming, et al.
Published: (2026)

Principled Synthetic Data Enables the First Scaling Laws for LLMs in Recommendation
by: Zhang, Benyu, et al.
Published: (2026)

Towards Scaling Laws for Symbolic Regression
by: Otte, David, et al.
Published: (2025)

Towards Robust Scaling Laws for Optimizers
by: Volkova, Alexandra, et al.
Published: (2026)

Towards Neural Scaling Laws for Time Series Foundation Models
by: Yao, Qingren, et al.
Published: (2024)

Wukong Framework for Not Safe For Work Detection in Text-to-Image systems
by: Liu, Mingrui, et al.
Published: (2025)

Towards a unified framework for guided diffusion models
by: Jiao, Yuchen, et al.
Published: (2025)

Towards Precise Scaling Laws for Video Diffusion Transformers
by: Yin, Yuanyang, et al.
Published: (2024)

Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima
by: Zhong, Shanshan, et al.
Published: (2024)

Two-dimensional Sparse Parallelism for Large Scale Deep Learning Recommendation Model Training
by: Zhang, Xin, et al.
Published: (2025)

SOLARIS: Speculative Offloading of Latent-bAsed Representation for Inference Scaling
by: Liu, Zikun, et al.
Published: (2026)

FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost
by: Feng, Chenhao, et al.
Published: (2026)

Scaling Laws for Speculative Decoding
by: Yan, Siyuan, et al.
Published: (2025)

MiniOneRec: An Open-Source Framework for Scaling Generative Recommendation
by: Kong, Xiaoyu, et al.
Published: (2025)

Towards Embodiment Scaling Laws in Robot Locomotion
by: Ai, Bo, et al.
Published: (2025)

A Graph-Theoretical Perspective on Law Design for Multiagent Systems
by: Shi, Qi, et al.
Published: (2025)

Unified Time Scale and Time Geometry:\\ Equivalence, Domains, and Solvable Models of Spectral--Scattering--Causal--Entropy
by: Ma, Haobo, et al.
Published: (2025)

Collective Memory and Conflict Transformation: Lessons From the Iraq‐Kuwait Conflict
by: Radhika Lakshminarayanan
Published: (2026)

TokenMixer-Large: Scaling Up Large Ranking Models in Industrial Recommenders
by: Jiang, Yuchen, et al.
Published: (2026)

Three-dimensional simulations of the parker instability in a uniformly-rotating disk
by: Jongsoo Kim
Published: (2000)