Transferring Knowledge from Large Foundation Models to Small Downstream
Models

Transferring Knowledge from Large Foundation Models to Small Downstream Models

11 June 2024

Danielle C. Maddix

Andrew Gordon Wilson

Papers citing "Transferring Knowledge from Large Foundation Models to Small Downstream Models"

6 / 6 papers shown

Title
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors Ravid Shwartz-Ziv Micah Goldblum Hossein Souri Sanyam Kapoor Chen Zhu Yann LeCun A. Wilson UQCV BDL 54 43 0 20 May 2022
Ranking and Tuning Pre-trained Models: A New Paradigm for Exploiting Model Hubs Kaichao You Yong Liu Ziyang Zhang Jianmin Wang Michael I. Jordan Mingsheng Long 98 30 0 20 Oct 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 239 2,554 0 04 May 2021
Show, Attend and Distill:Knowledge Distillation via Attention-based Feature Matching Mingi Ji Byeongho Heo Sungrae Park 56 140 0 05 Feb 2021
A linearized framework and a new benchmark for model selection for fine-tuning Aditya Deshpande Alessandro Achille Avinash Ravichandran Hao Li L. Zancato Charless C. Fowlkes Rahul Bhotika Stefano Soatto Pietro Perona ALM 105 46 0 29 Jan 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,927 0 20 Apr 2018