Influence Function Based Second-Order Channel Pruning-Evaluating True Loss Changes For Pruning Is Possible Without Retraining

13 August 2023

Papers citing "Influence Function Based Second-Order Channel Pruning-Evaluating True Loss Changes For Pruning Is Possible Without Retraining"

6 / 6 papers shown

Title
Benchmarking Post-Training Quantization in LLMs: Comprehensive Taxonomy, Unified Evaluation, and Comparative Analysis J. Zhao M. Wang Miao Zhang Yuzhang Shang Xuebo Liu Yaowei Wang Min Zhang Liqiang Nie MQ 60 1 0 18 Feb 2025
One Loss for Quantization: Deep Hashing with Discrete Wasserstein Distributional Matching Khoa D. Doan Peng Yang Ping Li MQ 23 37 0 31 May 2022
Natural Language Descriptions of Deep Visual Features Evan Hernandez Sarah Schwettmann David Bau Teona Bagashvili Antonio Torralba Jacob Andreas MILM 201 117 0 26 Jan 2022
Towards efficient end-to-end speech recognition with biologically-inspired neural networks Thomas Bohnstingl Ayush Garg Stanislaw Wo'zniak G. Saon E. Eleftheriou A. Pantazi 24 5 0 04 Oct 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 329 11,684 0 09 Mar 2017
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,198 0 01 Sep 2014