Unverified50% confidenceFactExact time
评估智能体编程能力的主流基准包括SWE-bench、SWE-bench Verified和HumanEval
1
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50%
Confidence
Long-term
Relevance
8/17/2026
First Seen
Sources
Related Claims
UnverifiedModel evaluations in the code generation field, such as HumanEval and SWE-bench, place special emphasis on functional correctness rather than fluency.79% similarUnverifiedThe most recognized evaluation benchmarks in the AI programming field include HumanEval (testing the generation of correct implementations from function docstrings) and SWE-bench (locating and fixing actual issues in real GitHub repositories).77% similarUnverified评估模型智能体能力的主流基准测试包括BFCL（Berkeley Function Calling Leaderboard）、AgentBench、SWE-Bench；编码能力评测集包括HumanEval、MBPP、LiveCodeBench76% similarUnverifiedSWE-bench involves high-level capabilities such as cross-file dependency analysis, version compatibility judgment, and regression test passing, making it more reflective of real engineering scenarios than function-writing benchmarks such as HumanEval75% similarVerifiedMainstream benchmarks for evaluating programming large models include HumanEval, MBPP, SWE-bench, and LiveCodeBench74% similar
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