R2SAEA fine-tunes an LLM with RL to reason about solution relations for surrogate-assisted evolutionary optimization, reporting improved relation prediction and SOTA performance on single- and multi-objective benchmarks.
Surrogate-assisted evolutionary computation: Recent advances and future challenges,
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SEETO achieves 6% better hypervolume in NWP parameter calibration with only 20 evaluations by using meteorological state representations for bi-level knowledge transfer from similar past tasks.
citing papers explorer
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Relation Reasoning with LLMs in Expensive Optimization
R2SAEA fine-tunes an LLM with RL to reason about solution relations for surrogate-assisted evolutionary optimization, reporting improved relation prediction and SOTA performance on single- and multi-objective benchmarks.
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Efficient Parameter Calibration of Numerical Weather Prediction Models via Evolutionary Sequential Transfer Optimization
SEETO achieves 6% better hypervolume in NWP parameter calibration with only 20 evaluations by using meteorological state representations for bi-level knowledge transfer from similar past tasks.