EvoPool
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EvoPool: Evolutionary Programmatic Annotation for Label-Efficient Specialized Supervision
arXiv:2606.01617v1 Announce Type: new Abstract: Large language models excel at general tasks but underperform smaller supervised models in specialized, high-stakes domains where training labels are costly. We address this regime with EvoPool, an evolutionary multi-agent framework inspired by Darwinian evolution. Three specialized agents iteratively propose executable annotator code, a small validation set provides a fitness signal, and a deterministic gate keeps only annotators that pass...