Transformers Power Summarization of Scientific Literature

Models like Longformer summarize lengthy research papers efficiently using sparse attention.

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🤯 Did You Know (click to read)

Sparse attention reduces memory usage from quadratic to linear in sequence length, making long document processing feasible.

Longformer employs sparse attention to reduce computational complexity, enabling Transformers to process thousands of tokens. This allows abstractive summarization and extraction of key information from long scientific documents without truncation.

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💥 Impact (click to read)

Summarization of long texts accelerates research by providing concise insights from entire papers, reports, or books.

Students, researchers, and professionals can quickly grasp important findings, improving productivity and knowledge acquisition.

Source

Beltagy et al., 2020 - Longformer

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