The gradient flow for linear in-context learning is derived in closed form, and two special cases are classified into attracting minima, saddle points, and invariant manifolds.
What can transformers learn in-context? a case study of simple function classes
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Dynamical Behaviors of the Gradient Flows for In-Context Learning
The gradient flow for linear in-context learning is derived in closed form, and two special cases are classified into attracting minima, saddle points, and invariant manifolds.