Asking LLMs to Verify First is Almost Free Lunch

• URL: http://arxiv.org/abs/2511.21734v1
• Date: Fri, 21 Nov 2025 09:55:34 GMT
• Title: Asking LLMs to Verify First is Almost Free Lunch
• Abstract summary: We introduce Verification-First (VF) to enhance the reasoning capabilities of Large Language Models (LLMs)<n>VF prompts models to verify a provided candidate answer, even a trivial or random one, before generating a solution.<n>We generalize the VF strategy to Iter-VF, a sequential test-time scaling (TTS) method that iteratively cycles the verification-generation process.
• Score: 36.15605737954829
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: To enhance the reasoning capabilities of Large Language Models (LLMs) without high costs of training, nor extensive test-time sampling, we introduce Verification-First (VF), a strategy that prompts models to verify a provided candidate answer, even a trivial or random one, before generating a solution. This approach triggers a "reverse reasoning" process that is cognitively easier and complementary to standard forward Chain-of-Thought (CoT), effectively invoking the model's critical thinking to reduce logical errors. We further generalize the VF strategy to Iter-VF, a sequential test-time scaling (TTS) method that iteratively cycles the verification-generation process using the model's previous answer. Extensive experiments across various benchmarks (from mathematical reasoning to coding and agentic tasks) and various LLMs (from open-source 1B to cutting-edge commercial ones) confirm that VF with random answer consistently outperforms standard CoT with minimal computational overhead, and Iter-VF outperforms existing TTS strategies.

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