Papers by Christian Igel

1 papers
MultiFin: A Dataset for Multilingual Financial NLP (2023.findings-eacl)

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Challenge: Multilingual models are needed to process financial text, which is produced across the world and requires a large dataset.
Approach: They propose to annotate a publicly available financial dataset using a hierarchical label structure and an annotation schema based on a real-world application.
Outcome: The proposed model can be used in high-resource languages, but there is room for improvement in low-resourced languages.

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