{
  "id": 17735902,
  "title": "LLM Detoxification via Transition-Aware Reward-Guided Representation Sampling",
  "url": "https://urgent.news/2026/10/30/llm-detoxification-via-transition-aware-reward-guided-representation",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-30T02:42:27.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.41165v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Large Language Models (LLMs) can generate toxic content, motivating effective test-time detoxification. Existing representation steering methods often rely on static or coarse interventions and provide imprecise guidance because they inadequately model transitions between toxic and non-toxic generations. We propose Transition-Aware Reward-Guided Representation Sampling (TARGRS), a test-time…",
  "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."
}