14 papers
Evaluating Structured Information Extraction with Open Models in a High Risk Public Sector Application
Elias Schubert, Felix Bießmann
The extraction of structured information from unstructured documents represents a critical component of digital transformations in all sectors. While proprietary solutions dominate…
Global Crises and National Policies: A Large Scale Analysis of Political Content in German Language Online Media
Yara Döring, Felix Bießmann
Today most media content is consumed based on algorithmic recommendations. Evidence suggests that this can lead to politically biased media consumption patterns. Automated extracti…
Redakto - The Incognito Tab for LLMs
Saurav Kumar Saha, Tom Röhr, Felix Bießmann
Large Language Models (LLMs) are being increasingly used in everyday applications. A major challenge in the context of LLMs or Artificial Intelligence (AI) in general is to ensure…
CURED: Creating, Understanding, and Repairing Errors Demonstrator
Nicholas Chandler, Sebastian Jäger, Philipp Jung +1
Detecting and cleaning errors in tabular data is a prerequisite for data intense software applications. Recent research at the intersection of Machine Learning (ML) and Database Ma…
A Resilient Solution for Sewer Overflow Monitoring across Cloud and Edge
Vipin Singh, Tianheng Ling, Peter Ghaly +3
Aging combined sewer systems in many historical cities are increasingly stressed by extreme rainfall events, which can trigger combined sewer overflows (CSO) with significant envir…
RamanBench: A Large-Scale Benchmark for Machine Learning on Raman Spectroscopy
Mario Koddenbrock, Christoph Lange, Robin Legner +6
Machine Learning (ML) has transformed many scientific fields, yet key applications still lack standardized benchmarks. Raman spectroscopy, a widely used technique for non-invasive…