Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers

15 March 2021

Papers citing "Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers"

6 / 6 papers shown

Title
Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries Yu-Hsiang Huang Yuche Tsai Hsiang Hsiao Hong-Yi Lin Shou-De Lin SILM 35 8 0 12 Jun 2024
Text Embeddings Reveal (Almost) As Much As Text John X. Morris Volodymyr Kuleshov Vitaly Shmatikov Alexander M. Rush RALM 26 94 0 10 Oct 2023
Spectral Bias in Practice: The Role of Function Frequency in Generalization Sara Fridovich-Keil Raphael Gontijo-Lopes Rebecca Roelofs 35 28 0 06 Oct 2021
Deduplicating Training Data Makes Language Models Better Katherine Lee Daphne Ippolito A. Nystrom Chiyuan Zhang Douglas Eck Chris Callison-Burch Nicholas Carlini SyDa 242 591 0 14 Jul 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 271 2,603 0 04 May 2021
A Learned Representation For Artistic Style Vincent Dumoulin Jonathon Shlens M. Kudlur GAN 214 1,156 0 24 Oct 2016