{
  "absUrl": "https://arxiv.org/abs/2610.39955v1",
  "arxivId": "2610.39955",
  "arxivVersion": 1,
  "arxivVersionedId": "2610.39955v1",
  "authors": [
    {
      "affiliations": [
        "Google Research"
      ],
      "name": "Subhashini Venugopalan"
    },
    {
      "affiliations": [
        "Google Research"
      ],
      "name": "Jenny Tan"
    },
    {
      "affiliations": [
        "Google Research"
      ],
      "name": "Taylor Roper"
    },
    {
      "affiliations": [
        "Google Research"
      ],
      "name": "Jimmy Tobin"
    },
    {
      "affiliations": [
        "Google Research"
      ],
      "name": "Anton Kast"
    },
    {
      "affiliations": [
        "Google Research"
      ],
      "name": "Alicia Martin"
    },
    {
      "affiliations": [
        "Google Research"
      ],
      "name": "Sam Sepah"
    },
    {
      "affiliations": [
        "Google Research",
        "UC Berkeley"
      ],
      "name": "Amy Pavel"
    }
  ],
  "contract": "researcher-sidecars-v1",
  "id": "2610.39955v1",
  "originalTitle": "Mind The Gap (MTG-AD): Dataset and Fine-grained Evaluation for End-to-End Inline Audio Descriptions",
  "pdfUrl": "https://arxiv.org/pdf/2610.39955v1.pdf",
  "schemaVersion": 1,
  "type": "preprint"
}