{
  "id": 5485349,
  "title": "Sequential Beats Joint: On the Interplay between On-Policy Distillation and RLVR",
  "url": "https://urgent.news/2026/09/03/sequential-beats-joint-on-the-interplay-between-on-policy",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-03T17:14:27.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.04108v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Reinforcement learning with verifiable rewards (RLVR) and on-policy distillation (OPD) have emerged as two dominant methods for post-training reasoning LLMs. Prior work uses OPD's dense token-level supervision to complement the sparse RL reward, fusing the two signals within a single step: either as a \\emph{weighted-additive combination} or a \\emph{teacher-modulated rescaling} of the RL…",
  "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."
}