{
  "id": 7691969,
  "title": "SKIP: a Self-knowledge-guided Step-wise Preference Learning Framework for Concise Reasoning",
  "url": "https://urgent.news/2026/09/15/skip-a-self-knowledge-guided-step-wise-preference-learning-framework",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-15T11:29:29.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.17019v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "While Chain-of-Thought (CoT) reasoning has been proven to be effective, it often leads to overthinking, resulting in computational overhead, inference latency, and even degraded performance in large language models (LLMs). Existing concise reasoning frameworks significantly compromise accuracy while compressing the length of output. In this paper, we propose SKIP, a self-knowledge-guided…",
  "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."
}