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How Much Does Attention Actually Attend? Questioning the Importance of Attention in Pretrained Transformers (2022.findings-emnlp)

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Challenge: Pretrained language models use the attention mechanism to contextualize input inputs . but, we find that it is not as important as thought for pretrained models .
Approach: They propose a probing method that replaces input-dependent attention matrices with constant ones.
Outcome: The proposed method improves performance of pretrained language models without input-dependent attention.

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