{
  "id": 4770761,
  "title": "Cost-efficient Active Learning for Referring Image Segmentation and Grounding",
  "url": "https://urgent.news/2026/08/31/cost-efficient-active-learning-for-referring-image-segmentation-and",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-31T11:29:28.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.30621v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Collecting natural-language referring expressions along with region annotations, such as masks or boxes, is a major bottleneck in visual grounding (VG), as annotators must write descriptions that distinguish target regions from visually similar ones. We tackle this by formulating active learning (AL) for VG under the realistic setting where only raw images are available without accompanying text.…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}