LLM syntax accuracy for LAMMPS scripts improved to 91% parser pass rate, yet only 1/80 scripts were scientifically correct on the hardest prompt; an agentic verification skill raised success to 5/6.
Grammar prompting for domain-specific language generation with large language models.Advances in Neural Information Processing Systems, 36:65030–65055
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Advanced language representations shape LLMs' schemas to improve knowledge activation and problem-solving.
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Evaluating LLM-generated code for domain-specific languages: molecular dynamics with LAMMPS
LLM syntax accuracy for LAMMPS scripts improved to 91% parser pass rate, yet only 1/80 scripts were scientifically correct on the hardest prompt; an agentic verification skill raised success to 5/6.
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Shaping Schema via Language Representation as the Next Frontier for LLM Intelligence Expanding
Advanced language representations shape LLMs' schemas to improve knowledge activation and problem-solving.