Scaling Laws for Sparsely-Connected Foundation Models

Scaling Laws for Sparsely-Connected Foundation Models

15 September 2023

Dan Alistarh

Papers citing "Scaling Laws for Sparsely-Connected Foundation Models"

18 / 18 papers shown

Title
UMoE: Unifying Attention and FFN with Shared Experts Yuanhang Yang Chaozheng Wang Jing Li MoE 29 0 0 12 May 2025
How can representation dimension dominate structurally pruned LLMs? Mingxue Xu Lisa Alazraki Danilo P. Mandic 56 0 0 06 Mar 2025
Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models Samira Abnar Harshay Shah Dan Busbridge Alaaeldin Mohamed Elnouby Ali J. Susskind Vimal Thilak MoE LRM 39 5 0 28 Jan 2025
Physics of Skill Learning Ziming Liu Yizhou Liu Eric J. Michaud Jeff Gore Max Tegmark 46 1 0 21 Jan 2025
Sparsing Law: Towards Large Language Models with Greater Activation Sparsity Yuqi Luo Chenyang Song Xu Han Y. Chen Chaojun Xiao Zhiyuan Liu Maosong Sun 49 3 0 04 Nov 2024
Scaling Laws for Predicting Downstream Performance in LLMs Yangyi Chen Binxuan Huang Yifan Gao Zhengyang Wang Jingfeng Yang Heng Ji LRM 43 8 0 11 Oct 2024
Scaling Optimal LR Across Token Horizons Johan Bjorck Alon Benhaim Vishrav Chaudhary Furu Wei Xia Song 54 4 0 30 Sep 2024
$$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts$ $\texttt{MoE-RBench}$ : Towards Building Reliable Language Models with Sparse Mixture-of-Experts Guanjie Chen Xinyu Zhao Tianlong Chen Yu Cheng MoE 71 5 0 17 Jun 2024
Effective Interplay between Sparsity and Quantization: From Theory to Practice Simla Burcu Harma Ayan Chakraborty Elizaveta Kostenok Danila Mishin Dongho Ha ... Martin Jaggi Ming Liu Yunho Oh Suvinay Subramanian Amir Yazdanbakhsh MQ 44 5 0 31 May 2024
Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance Jiasheng Ye Peiju Liu Tianxiang Sun Yunhua Zhou Jun Zhan Xipeng Qiu 46 62 0 25 Mar 2024
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 44 1 0 29 Nov 2023
A Simple and Effective Pruning Approach for Large Language Models Mingjie Sun Zhuang Liu Anna Bair J. Zico Kolter 62 355 0 20 Jun 2023
JaxPruner: A concise library for sparsity research Jooyoung Lee Wonpyo Park Nicole Mitchell Jonathan Pilault J. Obando-Ceron ... Hong-Seok Kim Yann N. Dauphin Karolina Dziugaite P. S. Castro Utku Evci 36 14 0 27 Apr 2023
Powerpropagation: A sparsity inducing weight reparameterisation Jonathan Richard Schwarz Siddhant M. Jayakumar Razvan Pascanu P. Latham Yee Whye Teh 90 54 0 01 Oct 2021
Accelerated Sparse Neural Training: A Provable and Efficient Method to Find N:M Transposable Masks Itay Hubara Brian Chmiel Moshe Island Ron Banner S. Naor Daniel Soudry 50 110 0 16 Feb 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 141 684 0 31 Jan 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 237 4,469 0 23 Jan 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,567 0 17 Apr 2017