Stochastic backtracking with subpool selection and power backtrack SMC over persistent prefix pools improves accuracy per token in PRM-guided test-time scaling for mathematical reasoning.
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Repeated sampling scales problem coverage log-linearly with sample count, improving SWE-bench Lite performance from 15.9% to 56% using 250 samples.
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Beyond the Frontier: Stochastic Backtracking for Efficient Test-Time Scaling
Stochastic backtracking with subpool selection and power backtrack SMC over persistent prefix pools improves accuracy per token in PRM-guided test-time scaling for mathematical reasoning.
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Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
Repeated sampling scales problem coverage log-linearly with sample count, improving SWE-bench Lite performance from 15.9% to 56% using 250 samples.