{
  "id": 16554911,
  "title": "A Foundation Model for Policy In-Context Longitudinal Causal Effect Estimation",
  "url": "https://urgent.news/2026/10/23/a-foundation-model-for-policy-in-context-longitudinal-causal-effect",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-23T16:34:49.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.32863v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Longitudinal causal effect estimation is complicated by time-varying confounding and treatment-confounder feedback loops. Existing methods generally require data-specific nuisance-model fitting, and many are tailored to prespecified treatment sequences or prediction horizons, leading to time-consuming computation at deployment. We introduce *Policy In-Context Longitudinal causal Effect estimation…",
  "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."
}