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    "headline": "Noisy Teammates Learned in Local Groups",
    "slug": "noisy-teammates-learned-in-local-groups",
    "dek": "SIGMA clusters cooperating agents before combining information across the full team.",
    "summary": "SIGMA clusters cooperating agents before combining information across the full team.",
    "body_text": "The framework starts from the claim that independent observation noise acquires local structure through task dependencies. It uses density-based grouping and within-group consensus to smooth agent-specific deviations, then integrates groups with attention. StarCraft II experiments reported stronger robustness under noisy observations while remaining competitive without noise. The evidence is simulation-based and does not establish robustness in open physical teams.",
    "why_it_matters": "SIGMA clusters cooperating agents before combining information across the full team.",
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      "The evidence is simulation-based and does not establish robustness in open physical teams."
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        "qualification": "The evidence is simulation-based and does not establish robustness in open physical teams."
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    "tags": [
      "multi-agent learning",
      "robustness",
      "observation noise"
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      "title": "arXiv preprint 2608.26683",
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      "published_at": "2026-08-27T02:40:42.000-04:00",
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    "description": "A daily newspaper for the age of artificial intelligence."
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    "title": "Noisy Teammates Learned in Local Groups",
    "publisher": "The Machine Press",
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