Algorithm Selection with Zero Domain Knowledge via Text Embeddings

Excerpt

arXiv:2604.19753v3 Announce Type: replace-cross Abstract: We propose ZeroFolio, a feature-free approach to algorithm selection that uses pretrained text embeddings instead of hand-crafted instance features. It reads the raw instance file as plain text, embeds it with a pretrained embedding model, and selects an algorithm via weighted k-nearest neighbors. Our approach is based on the observation that pretrained embeddings can distinguish problem instances without any domain knowledge or task-spec