CRUXEval-Output-CoT
CRUXEval-O (output prediction) with Chain-of-Thought prompting. Part of the CRUXEval benchmark consisting of 800 Python functions (3-13 lines) designed to evaluate code reasoning, understanding, and execution capabilities. The output prediction task requires models to predict the output of a given Python function with specific inputs, evaluated using chain-of-thought reasoning methodology.
Qwen2.5-Coder 7B Instruct from Alibaba Cloud / Qwen Team currently leads the CRUXEval-Output-CoT leaderboard with a score of 0.560 across 1 evaluated AI models.
What CRUXEval-Output-CoT measures
CRUXEval-Output-CoT is a text benchmark that evaluates large language models on reasoning tasks. LLM Stats tracks 1 model on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.6, with the leader reaching 0.6.
Compare leaders on the best AI for reasoning leaderboards.
Publication
- Paper
- CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
- Authors
- Alex Gu, Baptiste Rozière, Hugh Leather, Armando Solar-Lezama, and 2 others
- Published
- arXiv
- 2401.03065
Abstract
We present CRUXEval (Code Reasoning, Understanding, and eXecution Evaluation), a benchmark consisting of 800 Python functions (3-13 lines). Each function comes with an input-output pair, leading to two natural tasks: input prediction and output prediction. First, we propose a generic recipe for generating our execution benchmark which can be used to create future variation of the benchmark. Second, we evaluate twenty code models on our benchmark and discover that many recent high-scoring models on HumanEval do not show the same improvements on our benchmark. Third, we show that simple CoT and fine-tuning schemes can improve performance on our benchmark but remain far from solving it. The best setup, GPT-4 with chain of thought (CoT), achieves a pass@1 of 75% and 81% on input and output prediction, respectively. In contrast, Code Llama 34B achieves a pass@1 of 50% and 46% on input and output prediction, highlighting the gap between open and closed source models. As no model is close to acing CRUXEval, we provide examples of consistent GPT-4 failures on simple programs as a lens into its code reasoning capabilities and areas for improvement.
Qwen2.5-Coder 7B Instruct leads with 56.0%.
Progress Over Time
Interactive timeline showing model performance evolution on CRUXEval-Output-CoT
CRUXEval-Output-CoT Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Alibaba Cloud / Qwen Team | 7B | — | — |
FAQ
Common questions about CRUXEval-Output-CoT.
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