AI RESEARCH
SemanticOpt: Towards LLM-Based Semantic Black-Box Optimization
arXiv CS.AI
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ArXi:2510.25404v3 Announce Type: replace-cross Optimizing an experimental system can be extremely challenging when each experiment is expensive, time-consuming, or difficult to perform. Existing optimizers for expensive black-box problems, such as Bayesian optimization, are typically limited to numerical or categorical observations. They do not make use of broader domain knowledge, such as expert heuristics, relevant scientific papers, or similar previous experiments.