1k citations · 1.3k across the 56 of their papers we have counts for
12 papers · 1 filter
The Stable Artist: Steering Semantics in Diffusion Latent Space
Manuel Brack, Patrick Schramowski, Felix Friedrich +2
Large, text-conditioned generative diffusion models have recently gained a lot of attention for their impressive performance in generating high-fidelity images from text alone. How…
Speaking Multiple Languages Affects the Moral Bias of Language Models
Katharina Hämmerl, Björn Deiseroth, Patrick Schramowski +4
Pre-trained multilingual language models (PMLMs) are commonly used when dealing with data from multiple languages and cross-lingual transfer. However, PMLMs are trained on varying…
Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models
Patrick Schramowski, Manuel Brack, Björn Deiseroth +1
Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of ap…
LAION-5B: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu +13
Groundbreaking language-vision architectures like CLIP and DALL-E proved the utility of training on large amounts of noisy image-text data, without relying on expensive accurate la…
Revision Transformers: Instructing Language Models to Change their Values
Felix Friedrich, Wolfgang Stammer, Patrick Schramowski +1
Current transformer language models (LM) are large-scale models with billions of parameters. They have been shown to provide high performances on a variety of tasks but are also pr…
Exploiting Cultural Biases via Homoglyphs in Text-to-Image Synthesis
Lukas Struppek, Dominik Hintersdorf, Felix Friedrich +3
Models for text-to-image synthesis, such as DALL-E~2 and Stable Diffusion, have recently drawn a lot of interest from academia and the general public. These models are capable of p…