activity
20182025
most citedLow-Resource Text Classification using Domain-Adversarial Learning

26 citations · 26 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2025

A Toolbox for Improving Evolutionary Prompt Search

Daniel Grießhaber, Maximilian Kimmich, Johannes Maucher +1

Evolutionary prompt optimization has demonstrated effectiveness in refining prompts for LLMs. However, existing approaches lack robust operators and efficient evaluation mechanisms…

cs.AI2025

Anonymization of Documents for Law Enforcement with Machine Learning

Manuel Eberhardinger, Patrick Takenaka, Daniel Grießhaber +1

The steadily increasing utilization of data-driven methods and approaches in areas that handle sensitive personal information such as in law enforcement mandates an ever increasing…

cs.CV2024

Classification of Inkjet Printers based on Droplet Statistics

Patrick Takenaka, Manuel Eberhardinger, Daniel Grießhaber +1

Knowing the printer model used to print a given document may provide a crucial lead towards identifying counterfeits or conversely verifying the validity of a real document. Inkjet…

cs.CL2020

Fine-tuning BERT for Low-Resource Natural Language Understanding via Active Learning

Daniel Grießhaber, Johannes Maucher, Ngoc Thang Vu

Recently, leveraging pre-trained Transformer based language models in down stream, task specific models has advanced state of the art results in natural language understanding task…

cs.CL2018★ 26 cited

Low-Resource Text Classification using Domain-Adversarial Learning

Daniel Grießhaber, Ngoc Thang Vu, Johannes Maucher

Deep learning techniques have recently shown to be successful in many natural language processing tasks forming state-of-the-art systems. They require, however, a large amount of a…