{
  "id": 9055392,
  "title": "Triggers and Diagnostics for LLM-Based Interpretability Failures in Active Inference Agents",
  "url": "https://urgent.news/2026/09/19/triggers-and-diagnostics-for-llm-based-interpretability-failures-in",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-19T21:10:45.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.23215v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "LLM explainers are increasingly attached to autonomous agents as runtime oversight, with operators reading a generated account of the agent's beliefs and actions rather than its internal state. We audit the account itself, pairing an Active Inference (AIF) agent that tracks German grid demand and adjusts generation with an LLM explainer on three backends (GPT-4o, Claude-3-Opus, Gemini), and…",
  "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."
}