A CLIP-Powered Framework for Robust and Generalizable Data Selection

A CLIP-Powered Framework for Robust and Generalizable Data Selection

15 October 2024

Wanli Ouyang

Papers citing "A CLIP-Powered Framework for Robust and Generalizable Data Selection"

15 / 15 papers shown

Title
D2 Pruning: Message Passing for Balancing Diversity and Difficulty in Data Pruning A. Maharana Prateek Yadav Mohit Bansal 56 31 0 11 Oct 2023
Towards Sustainable Learning: Coresets for Data-efficient Deep Learning Yu Yang Hao Kang Baharan Mirzasoleiman 48 35 0 02 Jun 2023
Beyond neural scaling laws: beating power law scaling via data pruning Ben Sorscher Robert Geirhos Shashank Shekhar Surya Ganguli Ari S. Morcos 54 430 0 29 Jun 2022
Dataset Distillation by Matching Training Trajectories George Cazenavette Tongzhou Wang Antonio Torralba Alexei A. Efros Jun-Yan Zhu FedML DD 152 381 0 22 Mar 2022
Selective-Supervised Contrastive Learning with Noisy Labels Shikun Li Xiaobo Xia Shiming Ge Tongliang Liu NoLa 51 174 0 08 Mar 2022
Deep Learning on a Data Diet: Finding Important Examples Early in Training Mansheej Paul Surya Ganguli Gintare Karolina Dziugaite 81 446 0 15 Jul 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 656 28,659 0 26 Feb 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 307 40,217 0 22 Oct 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo D. Song Jacob Steinhardt Justin Gilmer OOD 252 1,715 0 29 Jun 2020
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 164 1,454 0 16 Jul 2019
On the Accuracy of Influence Functions for Measuring Group Effects Pang Wei Koh Kai-Siang Ang H. Teo Percy Liang TDI 57 186 0 30 May 2019
An Empirical Study of Example Forgetting during Deep Neural Network Learning Mariya Toneva Alessandro Sordoni Rémi Tachet des Combes Adam Trischler Yoshua Bengio Geoffrey J. Gordon 95 723 0 12 Dec 2018
Learning Transferable Architectures for Scalable Image Recognition Barret Zoph Vijay Vasudevan Jonathon Shlens Quoc V. Le 136 5,577 0 21 Jul 2017
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 607 36,599 0 25 Aug 2016
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 822 99,991 0 04 Sep 2014