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In this paper, we propose generalized attention mechanism (GAM) by firstsuggesting a new interpretation for self-attention mechanism of Vaswani et al.. Following the interpretation, we provide description for different variantsof attention mechanism which together form GAM. Further, we propose a newrelative position representation within the framework of GAM. Thisrepresentation can be easily utilized for cases in which elements next to eachother in input sequence can be at random locations in actual dataset/corpus.

Generalized Attention Mechanism and Relative Position for Transformer