TSGD-M stabilizes textual stochastic gradient descent by sampling past top-performing prompts through Gumbel-Top-k momentum and minibatch validation, improving prompt optimization across five benchmarks.
Incorporate feed- back into future responses through a brief internal re- view process
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Scaling Textual Gradients via Sampling-Based Momentum
TSGD-M stabilizes textual stochastic gradient descent by sampling past top-performing prompts through Gumbel-Top-k momentum and minibatch validation, improving prompt optimization across five benchmarks.