{
  "id": 8161612,
  "title": "Don't Mask the Environment: Observation Supervision Changes How Agents Explore Under RL",
  "url": "https://urgent.news/2026/09/17/dont-mask-the-environment-observation-supervision-changes-how-agents",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-17T17:11:29.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.20715v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Agent trajectories record what an agent does and what happens next. Yet standard supervised fine-tuning (SFT) applies loss only to agent-authored action tokens, using environment observations as context but not as prediction targets. We ask whether this convention provides the best initialization for subsequent reinforcement learning. We introduce ActObs, which also supervises the observation…",
  "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."
}