If you're spending extra tokens making an LLM critique itself, this paper says a simpler move can be better: just let it try again.

Before you make an LLM reflect on its answer, try giving it another independent attempt.

The study compares 7 test-time reasoning methods on Qwen2.5 models from 1.5B to 7B, then asks a fairer question: what happens if repeated sampling gets the same token budget?

Repeated sampling means solving the same math problem several times and taking the answer that shows up most often.

Across 36 comparisons, none of the more elaborate methods reliably beat that baseline at equal generated-token cost; 10 were significantly worse.

For checkable reasoning, extra tokens may be better spent creating independent attempts than asking the model to reconsider its own work.

Ofcouse, study boundary matters: this is Qwen2.5 on math, not frontier models or open-ended tasks.

• arxiv. org/abs/2607.28576

Title: "Sample More, Reflect Less: Self-Refine and Reflexion Lose to Repeated Sampling at Equal Token Cost, from 1.5B to 7B"