collaborators

6 papers

cs.CV2026

BAFIS: Dataset + Framework to assess occupational Bias and Human Preference in modern Text-to-image Models

Thomas Klassert, Adrian Ulges, Biying Fu

Generative artificial intelligence has the potential to improve productivity and transform the production of creative content. However, existing research indicates that image gener…

cs.CL2026

Agentic Insight Generation in VSM Simulations

Micha Selak, Dirk Krechel, Adrian Ulges +3

Extracting actionable insights from complex value stream map simulations can be challenging, time-consuming, and error-prone. Recent advances in large language models offer new ave…

cs.LG2026

DocDjinn: Controllable Synthetic Document Generation with VLMs and Handwriting Diffusion

Marcel Lamott, Saifullah Saifullah, Nauman Riaz +11

Effective document intelligence models rely on large amounts of annotated training data. However, procuring sufficient and high-quality data poses significant challenges due to the…

cs.SE2026

Exploring Generalizable Automated Program Repair with Large Language Models

Viola Campos, Ridwan Shariffdeen, Adrian Ulges +1

Automated Program Repair (APR) proposes bug fixes to aid developers in maintaining software. The state of the art in this domain focuses on LLMs, leveraging their strong capabiliti…

cs.SE2025

Multicalibration for LLM-based Code Generation

Viola Campos, Robin Kuschnereit, Adrian Ulges

As AI-based code generation becomes widespread, researchers are investigating the calibration of code LLMs - ensuring their confidence scores faithfully represent the true likeliho…

cs.LG2025

Integrating Expert Labels into LLM-based Emission Goal Detection: Example Selection vs Automatic Prompt Design

Marco Wrzalik, Adrian Ulges, Anne Uersfeld +2

We address the detection of emission reduction goals in corporate reports, an important task for monitoring companies' progress in addressing climate change. Specifically, we focus…