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Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of
  Latent-Based Diffusion Models

Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models

24 November 2023
Poyuan Mao
Shashank Kotyan
Tham Yik Foong
Danilo Vasconcellos Vargas
ArXivPDFHTML

Papers citing "Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models"

6 / 6 papers shown
Title
Alignment of Diffusion Models: Fundamentals, Challenges, and Future
Alignment of Diffusion Models: Fundamentals, Challenges, and Future
Buhua Liu
Shitong Shao
Bao Li
Lichen Bai
Zhiqiang Xu
Haoyi Xiong
James Kwok
Sumi Helal
Zeke Xie
45
12
0
11 Sep 2024
Beyond Aesthetics: Cultural Competence in Text-to-Image Models
Beyond Aesthetics: Cultural Competence in Text-to-Image Models
Nithish Kannen
Arif Ahmad
Marco Andreetto
Vinodkumar Prabhakaran
Utsav Prabhu
Adji Bousso Dieng
Pushpak Bhattacharyya
Shachi Dave
56
16
0
09 Jul 2024
Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models
Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models
Katherine Xu
Lingzhi Zhang
Jianbo Shi
43
12
0
23 May 2024
Breaking Free: How to Hack Safety Guardrails in Black-Box Diffusion
  Models!
Breaking Free: How to Hack Safety Guardrails in Black-Box Diffusion Models!
Shashank Kotyan
Poyuan Mao
Pin-Yu Chen
Danilo Vasconcellos Vargas
AAML
DiffM
43
0
0
07 Feb 2024
Diffusion-LM Improves Controllable Text Generation
Diffusion-LM Improves Controllable Text Generation
Xiang Lisa Li
John Thickstun
Ishaan Gulrajani
Percy Liang
Tatsunori B. Hashimoto
AI4CE
173
777
0
27 May 2022
RePaint: Inpainting using Denoising Diffusion Probabilistic Models
RePaint: Inpainting using Denoising Diffusion Probabilistic Models
Andreas Lugmayr
Martin Danelljan
Andrés Romero
Feng Yu
Radu Timofte
Luc Van Gool
DiffM
233
1,355
0
24 Jan 2022
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