{
  "id": 19078708,
  "title": "DexDICE: Reconciling Safety and Performance via Dual-Expert Offline Imitation Learning",
  "url": "https://urgent.news/2026/11/06/dexdice-reconciling-safety-and-performance-via-dual-expert-offline",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-06T13:04:30.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2611.09433v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Ensuring high returns while providing strong safety guarantees in offline imitation learning (IL) is a fundamental challenge: existing approaches either rely on explicitly specified cost functions, which are difficult to design for complex real-world safety constraints, or require expert demonstrations that are both safe and high-performing, which are often too costly to collect. We introduce…",
  "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."
}