Papers by Christina Viehmann

2 papers
AdapterHub Playground: Simple and Flexible Few-Shot Learning with Adapters (2022.acl-demo)

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Challenge: AdapterHub Playground is an open-access tool for researchers to use pretrained language models without writing a single line of code.
Approach: They propose a tool which allows researchers to leverage pretrained models without writing a single line of code for a variety of NLP tasks.
Outcome: The proposed model can be used for prediction, training and analysis of textual data without writing a single line of code.
Investigating label suggestions for opinion mining in German Covid-19 social media (2021.acl-long)

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Challenge: Existing difficulties in data annotation are due to prolonged data gathering processes or opinion surveys being subject to reactivity.
Approach: They propose to use label suggestions to improve annotation efficiency in german Covid-19 data by providing annotators with pre-recorded annotations.
Outcome: The proposed model improves inter-annotator agreement and annotation quality in a controlled study with social science students.

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