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AToken: A Unified Tokenizer for Vision
v1v2 (latest)

AToken: A Unified Tokenizer for Vision

Jiasen Lu
Liangchen Song
Mingze Xu
Byeongjoo Ahn
Yanjun Wang
Chen Chen
Afshin Dehghan
Yinfei Yang
    ViT
ArXiv (abs)PDFHTMLHuggingFace (27 upvotes)

Papers citing "AToken: A Unified Tokenizer for Vision"

3 / 3 papers shown
Title
Adapting Self-Supervised Representations as a Latent Space for Efficient Generation
Adapting Self-Supervised Representations as a Latent Space for Efficient Generation
Ming Gui
Johannes Schusterbauer
Timy Phan
Felix Krause
J. Susskind
Miguel Angel Bautista
Bjorn Ommer
108
0
0
16 Oct 2025
From Perception to Cognition: A Survey of Vision-Language Interactive Reasoning in Multimodal Large Language Models
From Perception to Cognition: A Survey of Vision-Language Interactive Reasoning in Multimodal Large Language Models
Chenyue Zhou
Mingxuan Wang
Yanbiao Ma
Chenxu Wu
Wanyi Chen
...
Guoli Jia
Lingling Li
Z. Lu
Y. Lu
Wenhan Luo
LRM
290
1
0
29 Sep 2025
Aligning Visual Foundation Encoders to Tokenizers for Diffusion Models
Aligning Visual Foundation Encoders to Tokenizers for Diffusion Models
Bowei Chen
Sai Bi
Hao Tan
He Zhang
Tianyuan Zhang
Zhengqi Li
Yuanjun Xiong
Jianming Zhang
Kai Zhang
104
1
0
29 Sep 2025