DenoiseRotator: Enhance Pruning Robustness for LLMs via Importance Concentration

29 May 2025

Papers citing "DenoiseRotator: Enhance Pruning Robustness for LLMs via Importance Concentration"

7 / 7 papers shown

Title
SpinQuant: LLM quantization with learned rotations Zechun Liu Changsheng Zhao Igor Fedorov Bilge Soran Dhruv Choudhary Raghuraman Krishnamoorthi Vikas Chandra Yuandong Tian Tijmen Blankevoort MQ 160 105 0 21 Feb 2025
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models Yifei Liu Jicheng Wen Yang Wang Shengyu Ye Li Lyna Zhang Ting Cao Cheng Li Mao Yang MQ 164 12 0 25 Sep 2024
Geoopt: Riemannian Optimization in PyTorch Max Kochurov R. Karimov Sergei Kozlukov 36 118 0 06 May 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 118 42,038 0 03 Dec 2019
Riemannian Adaptive Optimization Methods Gary Bécigneul O. Ganea ODL 78 254 0 01 Oct 2018
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 314 129,831 0 12 Jun 2017
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Song Han Huizi Mao W. Dally 3DGS 172 8,793 0 01 Oct 2015