SeiT++: Masked Token Modeling Improves Storage-efficient Training

15 December 2023

Papers citing "SeiT++: Masked Token Modeling Improves Storage-efficient Training"

6 / 6 papers shown

Title
Muse: Text-To-Image Generation via Masked Generative Transformers Huiwen Chang Han Zhang Jarred Barber AJ Maschinot José Lezama ... Kevin Patrick Murphy William T. Freeman Michael Rubinstein Yuanzhen Li Dilip Krishnan DiffM 197 519 0 02 Jan 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 305 7,434 0 11 Nov 2021
Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective Luca Scimeca Seong Joon Oh Sanghyuk Chun Michael Poli Sangdoo Yun OOD 381 49 0 06 Oct 2021
Dataset Condensation with Differentiable Siamese Augmentation Bo-Lu Zhao Hakan Bilen DD 196 288 0 16 Feb 2021
Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision Chao Jia Yinfei Yang Ye Xia Yi-Ting Chen Zarana Parekh Hieu H. Pham Quoc V. Le Yun-hsuan Sung Zhen Li Tom Duerig VLM CLIP 298 3,693 0 11 Feb 2021
Semantic Understanding of Scenes through the ADE20K Dataset Bolei Zhou Hang Zhao Xavier Puig Tete Xiao Sanja Fidler Adela Barriuso Antonio Torralba SSeg 253 1,827 0 18 Aug 2016