The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of Attention https://arxiv.org/abs/2202.05798
Another piece of the puzzle seems to be transformer "induction heads" where attention heads in consecutive layers work together to provide a mechanism that is believed to be responsible for much of in-context learning. The idea is that earlier instances of a token pattern/sequence in the context are used to predict the continuation of a similar pattern later on.
In the most simple case this is a copying operation such that an early occurrence of AB predicts that a later A should be followed by B. In the more general case this becomes A'B' => AB which seems to be more of an analogy type relationship.
Transformer Feed-Forward Layers Are Key-Value Memories https://arxiv.org/abs/2012.14913
The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of Attention https://arxiv.org/abs/2202.05798
https://github.com/neelnanda-io/TransformerLens