{
  "id": 19772772,
  "title": "AgentSSL: Can MLE Agents Leverage Unlabeled Data?",
  "url": "https://urgent.news/2026/11/12/agentssl-can-mle-agents-leverage-unlabeled-data",
  "topic": "finance",
  "section": "Finance & Markets",
  "published": "2026-11-12T18:59:06.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2611.17323v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Applying machine learning systems to new domains introduces bottlenecks in both labeled data acquisition and manual pipeline engineering. While recent MLE agents show promise in automating pipeline design, they have been studied almost exclusively in fully supervised settings, leaving them untested in realistic regimes where labeled data is scarce but unlabeled data is abundant. In this work, we…",
  "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."
}