Papers with information consumption

2 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.
HIBRIDS: Attention with Hierarchical Biases for Structure-aware Long Document Summarization (2022.acl-long)

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Challenge: Document structure is critical for efficient information consumption, but it is difficult to encode it efficiently into the modern Transformer architecture.
Approach: They propose a task which injects Hierarchical Biases foR Incorporating Document Structure into attention score calculation.
Outcome: The proposed model produces better question-summary hierarchies than comparisons on hierarchy quality and content coverage, the authors show .

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