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    "headline": "Industrial Configuration Needs More Than a Language Model",
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    "dek": "A survey organized neuro-symbolic copilot designs around inference, fine-tuning and training-time integration.",
    "summary": "A survey organized neuro-symbolic copilot designs around inference, fine-tuning and training-time integration.",
    "body_text": "The preprint argues that unconstrained language generation is too unreliable for configuration work governed by compatibility rules, catalogs and engineering limits. It classifies hybrid systems by where symbolic knowledge enters: at inference, during fine-tuning or inside training objectives. An industrial configuration copilot grounds the discussion, while the paper also flags scaling, maintenance and evaluation problems that remain unresolved.",
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      "An industrial configuration copilot grounds the discussion, while the paper also flags scaling, maintenance and evaluation problems that remain unresolved."
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      "neuro-symbolic AI",
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      "title": "arXiv preprint 2609.29947",
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    "title": "Industrial Configuration Needs More Than a Language Model",
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