Summary
A new benchmark has been developed to rigorously test Large Language Models (LLMs) on their understanding and application of 28 physics laws. This benchmark generates adversarial questions designed to expose common LLM weaknesses, such as anchoring bias and unit confusion. It uses symbolic math libraries like sympy and pint for objective grading, ensuring accuracy without relying on LLM-as-judge methods.
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