Transformer weights at early training stages are closed-form compositions of bigram, token-interchangeability, and context mappings that directly reflect text-corpus statistics and explain the emergence of semantic associations.
As in the one-layer bound, we can use the bound on the attention pattern to controlJ (l) i
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How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability
Transformer weights at early training stages are closed-form compositions of bigram, token-interchangeability, and context mappings that directly reflect text-corpus statistics and explain the emergence of semantic associations.