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Forget generic pre-training: Speculative decoding gets a serious speed boost when your draft model is a specialist trained on data matching the target task.
LLMs still struggle to generalize quantum code generation across frameworks like Qiskit, PennyLane, and Cirq, even with feedback-based repair pushing performance to 83.3%, 76.2%, and 66.7% respectively.
