AI RESEARCH
QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation
arXiv CS.AI
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ArXi:2604.08570v1 Announce Type: cross Large Language Models (LLMs) are increasingly used for code generation, yet quantum code generation is still evaluated mostly within single frameworks, making it difficult to separate quantum reasoning from framework familiarity. We We evaluate models with executable functional tests, report Pass and Pass, and use KL-divergence-based acceptance for probabilistic outputs. We additionally study Pass after feedback-based repair, where a model may revise code after a runtime error or wrong answer.