[magicalhippo]

The visualization reveals that Transformer tends to allocate only a small proportion of attention scores to the correct answer, while disproportionately focusing on irrelevant context.

[...] Specifically, we partition the query and key vectors into two groups and compute two separate softmax attention maps. Then the result of subtracting these two maps is regarded as attention scores.

[...] The approach is analogous to noise-canceling headphones and differential amplifiers in electrical engineering, where the difference between two signals cancels out common-mode noise.

Simple change, with seemingly decent improvements across the board.