Papers by Roberto Ulloa

1 papers
Assessing In-context Learning and Fine-tuning for Topic Classification of German Web Data (2024.acl-srw)

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Challenge: Using a few hundred annotated data points per topic, we detect content related to three German policies in a database of scraped webpages.
Approach: They propose to use annotated data to train a binary classification task to detect topic-related content in a scraped database of webpages.
Outcome: The proposed model detects content related to three German policies in a scraped database of scrapes of webpages using a few hundred annotated data points per topic.

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