ACING uses off-policy actor-critic RL over continuous latent vectors, decoded by a frozen white-box model, to optimize discrete instructions for black-box LLMs from reward feedback alone.
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ACING: Actor-Critic for Instruction Learning in Black-Box LLMs
ACING uses off-policy actor-critic RL over continuous latent vectors, decoded by a frozen white-box model, to optimize discrete instructions for black-box LLMs from reward feedback alone.