{
  "id": 10351547,
  "title": "Different Corruptions, Different Signals: Uncertainty and Loss in Federated Data Quality",
  "url": "https://urgent.news/2026/09/25/different-corruptions-different-signals-uncertainty-and-loss-in",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-25T16:09:21.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.31454v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Federated learning (FL) data corruption can affect either inputs or labels, but it remains unclear whether input-conditional uncertainty and prediction-label loss expose these corruption modes equally. This paper compares two corruption-detection signals in FL: input-conditional uncertainty and prediction-label loss. The uncertainty signal is characterised using a learned aleatoric variance…",
  "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."
}