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This work explores whether LLMs can accurately predict and explain plausible materials for vehicle components such as brake discs or fuel injectors without requiring extensive fine-tuning and substantially outperforms prior work.
LLMs will readily twist implausible events into plausible metaphors, revealing a surprising gap in their grasp of real-world constraints compared to humans.