{
  "absUrl": "https://arxiv.org/abs/2609.32788v1",
  "arxivId": "2609.32788",
  "arxivVersion": 1,
  "arxivVersionedId": "2609.32788v1",
  "authors": [
    {
      "affiliations": [
        "Yale University",
        "New Haven, CT"
      ],
      "name": "Chao Peter Yang"
    },
    {
      "affiliations": [
        "Duke University",
        "Durham, NC"
      ],
      "name": "Cynthia Rudin"
    },
    {
      "affiliations": [
        "Duke University",
        "Durham, NC"
      ],
      "name": "Yue Jiang"
    },
    {
      "affiliations": [
        "Duke University",
        "Durham, NC"
      ],
      "name": "Simon Mak"
    },
    {
      "affiliations": [
        "Chinese University of Hong Kong, Shenzhen",
        "Shenzhen, Guangdong"
      ],
      "name": "Stephen Ni-Hahn"
    }
  ],
  "contract": "researcher-sidecars-v1",
  "id": "2609.32788v1",
  "originalTitle": "Getting Motif-ated: Controllable AI Compositions from Injected Motif Prompts",
  "pdfUrl": "https://arxiv.org/pdf/2609.32788v1.pdf",
  "schemaVersion": 1,
  "type": "preprint"
}