{
  "id": 16704987,
  "title": "Profiling a Frontier Agent with EBench: From Direct Control to Harness with Policy",
  "url": "https://urgent.news/2026/10/26/profiling-a-frontier-agent-with-ebench-from-direct-control-to-harness",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-26T17:51:02.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2610.35832v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Frontier multimodal large language models (MLLMs) can control robots without robot-specific training, but how their capabilities compare and interact with post-trained vision-language-action (VLA) and world action model (WAM) policies across manipulation demands remains to be thoroughly evaluated. In this report, we evaluate GPT-6-Astra on EBench as the core of an agent that controls a robot…",
  "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."
}