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[D] What is the inductive bias in transformer architectures?

I’ve been thinking a lot about the question of inductive biases recently; basically equipping a model with a set of assumptions in order to make it prefer certain solutions. This can happen in different ways, like the model architecture, the loss or regularization.

In NLP, RNNs are (still) very popular because through their recurrency they exhibit an inductive bias that makes them temporally invariant, but recent work (like this) seems to suggest that this way they also suffer from a recency bias, which might inhibit their application to language.

Now that transformers dominate the leaderboards in many NLP tasks, I was wondering which kind of inductive bias they might carry given their architecture?

submitted by /u/Kaleidophon
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.