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arXiv AI By Bo Ni

Learning from fracture: Teaching language models to design through physical experience

Read the original on arXiv AI →

The paper introduces FracLearn, a framework that enables language models to design physical structures by learning from simulated fracture experiments. In a Tetris-inspired fracture game, the model proposes architectures, gathers experience from simulated crack responses, abstracts observations into conditional principles, and generalizes these principles to create improved designs. The approach achieves a 11.0% performance gain over prior records and demonstrates that learning can occur through external knowledge and decision-making without updating model weights.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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