Beyond Repeated Sampling: Scaling LLM Test-Time Reasoning With Learned Concepts
rbhar90 · x · 2026-09-24
A new paper argues repeated sampling, the default way to scale LLM reasoning at test time, is inefficient: token-level noise yields many near-duplicate attempts following the same high-level idea. The authors propose guiding sampling with learned concepts to cover more of the solution space without sacrificing throughput.
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