Greedy Output Approximation: Towards Efficient Structured Pruning for LLMs Without Retraining

26 July 2024

Papers citing "Greedy Output Approximation: Towards Efficient Structured Pruning for LLMs Without Retraining"

9 / 9 papers shown

Title
SVD-LLM V2: Optimizing Singular Value Truncation for Large Language Model Compression Xin Wang Samiul Alam Zhongwei Wan H. Shen M. Zhang MQ 59 0 0 16 Mar 2025
SEAP: Training-free Sparse Expert Activation Pruning Unlock the Brainpower of Large Language Models Xun Liang Hanyu Wang Huayi Lai Simin Niu Shichao Song Jiawei Yang Jihao Zhao Feiyu Xiong Bo Tang Z. Li VLM 45 0 0 10 Mar 2025
Superficial Safety Alignment Hypothesis Jianwei Li Jung-Eun Kim 24 1 0 07 Oct 2024
Subspace Node Pruning Joshua Offergeld Marcel van Gerven Nasir Ahmad 36 0 0 26 May 2024
Shortened LLaMA: Depth Pruning for Large Language Models with Comparison of Retraining Methods Bo-Kyeong Kim Geonmin Kim Tae-Ho Kim Thibault Castells Shinkook Choi Junho Shin Hyoung-Kyu Song 54 30 0 05 Feb 2024
SliceGPT: Compress Large Language Models by Deleting Rows and Columns Saleh Ashkboos Maximilian L. Croci Marcelo Gennari do Nascimento Torsten Hoefler James Hensman VLM 125 145 0 26 Jan 2024
DepGraph: Towards Any Structural Pruning Gongfan Fang Xinyin Ma Mingli Song Michael Bi Mi Xinchao Wang GNN 79 256 0 30 Jan 2023
Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding Mengnan Du Subhabrata Mukherjee Yu Cheng Milad Shokouhi Xia Hu Ahmed Hassan Awadallah 44 13 0 16 Oct 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 139 684 0 31 Jan 2021