Transformers develop four algorithmic phases of in-context learning on Markov chains via two distinct multi-layer subcircuit mechanisms, with phase boundaries set by data diversity K.
To do so, we developed a custom Python implementation of the model forward pass that explicitly exposes the vector passed along each layer connection
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Distinct mechanisms underlying in-context learning in transformers
Transformers develop four algorithmic phases of in-context learning on Markov chains via two distinct multi-layer subcircuit mechanisms, with phase boundaries set by data diversity K.