activity
20222024
most citedHolistic Evaluation of Text-To-Image Models

13 citations · 43 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2024★ 1 cited

Arabic Stable LM: Adapting Stable LM 2 1.6B to Arabic

Zaid Alyafeai, Michael Pieler, Hannah Teufel +8

Large Language Models (LLMs) have shown impressive results in multiple domains of natural language processing (NLP) but are mainly focused on the English language. Recently, more L…

cs.CL2024★ 1 cited

Rephrasing natural text data with different languages and quality levels for Large Language Model pre-training

Michael Pieler, Marco Bellagente, Hannah Teufel +9

Recently published work on rephrasing natural text data for pre-training LLMs has shown promising results when combining the original dataset with the synthetically rephrased data.…

cs.CL2024★ 8 cited

Stable LM 2 1.6B Technical Report

Marco Bellagente, Jonathan Tow, Dakota Mahan +16

We introduce StableLM 2 1.6B, the first in a new generation of our language model series. In this technical report, we present in detail the data and training procedure leading to…

cs.CV2023★ 13 cited

Holistic Evaluation of Text-To-Image Models

Tony Lee, Michihiro Yasunaga, Chenlin Meng +15

The stunning qualitative improvement of recent text-to-image models has led to their widespread attention and adoption. However, we lack a comprehensive quantitative understanding…

cs.CL2023★ 7 cited

Quality-Diversity through AI Feedback

Herbie Bradley, Andrew Dai, Hannah Teufel +7

In many text-generation problems, users may prefer not only a single response, but a diverse range of high-quality outputs from which to choose. Quality-diversity (QD) search algor…

cs.CV2023★ 6 cited

MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation

Marco Bellagente, Manuel Brack, Hannah Teufel +11

The recent popularity of text-to-image diffusion models (DM) can largely be attributed to the intuitive interface they provide to users. The intended generation can be expressed in…

cs.CV2022★ 7 cited

M-VADER: A Model for Diffusion with Multimodal Context

Samuel Weinbach, Marco Bellagente, Constantin Eichenberg +7

We introduce M-VADER: a diffusion model (DM) for image generation where the output can be specified using arbitrary combinations of images and text. We show how M-VADER enables the…

cs.CV2022

Comparison of synthetic dataset generation methods for medical intervention rooms using medical clothing detection as an example

Patrick Schülein, Hannah Teufel, Ronja Vorpahl +7

The availability of real data from areas with high privacy requirements, such as the medical intervention space, is low and the acquisition legally complex. Therefore, this work pr…