Survey of RLM adoption in 28 disciplines reveals maturity disparities via a new assessment framework, with focus on development, evaluation, and public resources.
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ALL-FEM fine-tunes LLMs on a corpus of verified FEniCS scripts and uses multi-agent workflows to automate finite element code generation, achieving 71.79% success on 39 benchmarks across elasticity, flow, and coupled problems.
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Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches
Survey of RLM adoption in 28 disciplines reveals maturity disparities via a new assessment framework, with focus on development, evaluation, and public resources.