{
  "id": 14857885,
  "title": "Learning to Steer LLM Agents and Multi-Agent Systems",
  "url": "https://urgent.news/2026/10/15/learning-to-steer-llm-agents-and-multi-agent-systems",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-15T17:51:17.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.22316v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Large language model (LLM)-based agents and multi-agent systems increasingly tackle complex tasks through long-horizon tool use and inter-agent collaboration. However, these systems are prone to deviating from the overall goal as execution unfolds, which wastes execution resources and leads to undesired outcomes, a failure termed goal drift. In this work, we propose a steering agent that…",
  "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."
}