{
  "schema_version": "1.0",
  "id": "archive:https://arxiv.org/abs/2607.02510v1",
  "slug": "2607-02510v1-1ppjdya",
  "url": "https://feed7.dev/p/2607-02510v1-1ppjdya",
  "title": "Online Safety Monitoring for LLMs",
  "why_included": "A deliberately simple online safety monitor — threshold an external verifier's signal, calibrate via risk control — matches sequential-hypothesis-testing monitors on math-reasoning and red-teaming datasets.",
  "summary": "**The gist** The monitor turns an **external verifier model's** score into an alarm by **thresholding**, with the threshold calibrated through **risk control** for statistical guarantees. On **math reasoning and red-teaming** datasets it is competitive with more elaborate **sequential hypothesis testing** monitors.",
  "practical_implication": "**Why it matters** If you run agents in production, this is evidence that runtime safety monitoring doesn't need exotic machinery: a verifier plus a **calibrated threshold** yields a principled alarm with formal risk bounds — a pattern that drops into an existing gateway or eval pipeline.",
  "agent_context": "**The gist** The monitor turns an **external verifier model's** score into an alarm by **thresholding**, with the threshold calibrated through **risk control** for statistical guarantees. On **math reasoning and red-teaming** datasets it is competitive with more elaborate **sequential hypothesis testing** monitors.\n\n**Why it matters** If you run agents in production, this is evidence that runtime safety monitoring doesn't need exotic machinery: a verifier plus a **calibrated threshold** yields a principled alarm with formal risk bounds — a pattern that drops into an existing gateway or eval pipeline.\n\n**Watch out** Everything rides on the **verifier's quality** and on calibration data matching deployment traffic; results cover just **two datasets**, and this is workshop-stage work, so generalization is unproven.",
  "source": {
    "name": "arXiv",
    "url": "https://arxiv.org/abs/2607.02510v1",
    "published_at": null
  },
  "source_class": "blog_post",
  "content_type": "Paper",
  "layer": "benchmark",
  "domains": [
    "research",
    "security"
  ],
  "topics": [
    "agent-reliability",
    "observability"
  ],
  "verification": {
    "status": "needs_review",
    "label": "Needs Review",
    "method": "unverified",
    "verified_at": null
  },
  "uncertainty": [
    "Everything rides on the **verifier's quality** and on calibration data matching deployment traffic; results cover just **two datasets**, and this is workshop-stage work, so generalization is unproven."
  ],
  "lifecycle": "Current",
  "published_at": null,
  "modified_at": null,
  "supersedes": [],
  "expires_at": null,
  "formats": {
    "html": "https://feed7.dev/p/2607-02510v1-1ppjdya",
    "json": "https://feed7.dev/p/2607-02510v1-1ppjdya.json",
    "markdown": "https://feed7.dev/p/2607-02510v1-1ppjdya.md"
  }
}