Supervised fine-tuning on gate-by-gate quantum simulation traces allows LLMs to achieve near-perfect accuracy in predicting quantum measurement outcomes, with added GRPO improving generalization to larger qubit counts.
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Fine-Tuning Large Language Models for Quantum Reasoning
Supervised fine-tuning on gate-by-gate quantum simulation traces allows LLMs to achieve near-perfect accuracy in predicting quantum measurement outcomes, with added GRPO improving generalization to larger qubit counts.