AI RESEARCH
An Execution-Verified Multi-Language Benchmark for Code Semantic Reasoning
arXiv CS.AI
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ArXi:2605.11006v1 Announce Type: cross Evaluating whether large language models (LLMs) can recover execution-relevant program structure, rather than only produce code that passes tests, remains an open problem. Existing code benchmarks emphasize test-passing outputs, from standalone programming tasks (HumanEval, MBPP, LiveCodeBench) to repository repair (SWE-Bench); this is useful, but offers limited diagnostic signal about which program semantics a model can recover from source. We.