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# Big Bird: Transformers for Longer Sequences | ||
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We propose, BigBird, a sparse attention mechanism that reduces this quadratic | ||
dependency to linear. We show that BigBird is a universal approximator of | ||
sequence functions and is Turing complete, thereby preserving these properties | ||
of the quadratic, full attention model. The proposed sparse attention can | ||
handle sequences of length up to 8x of what was previously possible using | ||
similar hardware. As a consequence of the capability to handle longer context, | ||
BigBird drastically improves performance on various NLP tasks such as question | ||
answering and summarization. | ||
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Code release in progress. |