Author

Timothy Baldwin

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Jul 2026

In-Context Learning as Implicit Policy Gradient

It is shown that score-conditioned In-Context Learning (ICL) admits a structural correspondence to policy gradient optimization, and an exact upper bound on the distribution shift induced by a bounded attention update is derived, yielding a trust-region-like analogy to KL-constrained policy optimization.

Masahiro Kaneko, Timothy Baldwin · arXiv.org · 0 citations