4 papers
Reassessing Active Learning Adoption in Contemporary NLP: A Community Survey
Julia Romberg, Christopher Schröder, Julius Gonsior +2
Supervised learning relies on data annotation which usually is time-consuming and therefore expensive. A longstanding strategy to reduce annotation costs is active learning, an ite…
Text Annotation Handbook: A Practical Guide for Machine Learning Projects
Felix Stollenwerk, Joey Öhman, Danila Petrelli +5
This handbook is a hands-on guide on how to approach text annotation tasks. It provides a gentle introduction to the topic, an overview of theoretical concepts as well as practical…
We Need to Talk About Data: The Importance of Data Readiness in Natural Language Processing
Fredrik Olsson, Magnus Sahlgren
In this paper, we identify the state of data as being an important reason for failure in applied Natural Language Processing (NLP) projects. We argue that there is a gap between ac…
Exploring the Assessment List for Trustworthy AI in the Context of Advanced Driver-Assistance Systems
Markus Borg, Joshua Bronson, Linus Christensson +5
Artificial Intelligence (AI) is increasingly used in critical applications. Thus, the need for dependable AI systems is rapidly growing. In 2018, the European Commission appointed…