L0-Reasoning Bench: Evaluating Procedural Correctness in Language Models via Simple Program Execution

• URL: http://arxiv.org/abs/2503.22832v2
• Date: Thu, 10 Apr 2025 18:45:37 GMT
• Title: L0-Reasoning Bench: Evaluating Procedural Correctness in Language Models via Simple Program Execution
• Authors: Simeng Sun, Cheng-Ping Hsieh, Faisal Ladhak, Erik Arakelyan, Santiago Akle Serano, Boris Ginsburg,
• Abstract summary: Complex reasoning tasks often rely on the ability to consistently and accurately apply simple rules across incremental steps.<n>We introduce L0-Bench, a language model benchmark for testing procedural correctness.<n>L0-Bench grades models on their ability to generate step-by-step, error-free execution traces.
• Score: 31.19899557805607
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Complex reasoning tasks often rely on the ability to consistently and accurately apply simple rules across incremental steps, a foundational capability which we term "level-0" reasoning. To systematically evaluate this capability, we introduce L0-Bench, a language model benchmark for testing procedural correctness -- the ability to generate correct reasoning processes, complementing existing benchmarks that primarily focus on outcome correctness. Given synthetic Python functions with simple operations, L0-Bench grades models on their ability to generate step-by-step, error-free execution traces. The synthetic nature of L0-Bench enables systematic and scalable generation of test programs along various axes (e.g., number of trace steps). We evaluate a diverse array of recent closed-source and open-weight models on a baseline test set. All models exhibit degradation as the number of target trace steps increases, while larger models and reasoning-enhanced models better maintain correctness over multiple steps. Additionally, we use L0-Bench to explore test-time scaling along three dimensions: input context length, number of solutions for majority voting, and inference steps. Our results suggest substantial room to improve "level-0" reasoning and potential directions to build more reliable reasoning systems.

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