5 papers
Reading Between the Tokens: Improving Preference Predictions through Mechanistic Forecasting
Sarah Ball, Simeon Allmendinger, Niklas Kühl +2
Large language models are increasingly used to predict human preferences in both scientific and business endeavors, yet current approaches rely exclusively on analyzing model outpu…
PromptPilot: Improving Human-AI Collaboration Through LLM-Enhanced Prompt Engineering
Niklas Gutheil, Valentin Mayer, Leopold Müller +2
Effective prompt engineering is critical to realizing the promised productivity gains of large language models (LLMs) in knowledge-intensive tasks. Yet, many users struggle to craf…
Data Quality Challenges in Retrieval-Augmented Generation
Leopold Müller, Joshua Holstein, Sarah Bause +2
Organizations increasingly adopt Retrieval-Augmented Generation (RAG) to enhance Large Language Models with enterprise-specific knowledge. However, current data quality (DQ) framew…
Do Edges Matter? Investigating Edge-Enhanced Pre-Training for Medical Image Segmentation
Paul Zaha, Lars Böcking, Simeon Allmendinger +2
Medical image segmentation is crucial for disease diagnosis and treatment planning, yet developing robust segmentation models often requires substantial computational resources and…
Utilizing Data Fingerprints for Privacy-Preserving Algorithm Selection in Time Series Classification: Performance and Uncertainty Estimation on Unseen Datasets
Lars Böcking, Leopold Müller, Niklas Kühl
The selection of algorithms is a crucial step in designing AI services for real-world time series classification use cases. Traditional methods such as neural architecture search,…