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TIRE: Top-Down Formula Instantiation with Reliable Execution for Physics Problem Synthesis
Advancing physics reasoning in large language models requires scalable training data that connect physical laws, concrete problem scenarios, and verifiable numerical answers. Expert-designed problems offer top-down control over physical laws, conditions, and scenarios, but require costly human effor
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