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EMNLP_Cost-Aware-Protocol-Routing

Scikit-learn
Joblib
English
protocol-routing
llm-routing
multi-agent-systems
cost-aware-inference
protocol-selection
calibration
reasoning
reproducibility
emnlp2026
Model card Files
xet
 Community
EMNLP_Cost-Aware-Protocol-Routing
File size: 3,126 Bytes
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{
  "artifact": "metadata-only protocol router (multinomial logistic regression)",
  "task": "predict the fixed-order-oracle action for a problem, before any protocol runs",
  "actions": [
    "baseline_llm",
    "single_agent",
    "per",
    "broadcast",
    "none"
  ],
  "n_features_in": 220,
  "feature_blocks": [
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      "type": "OneHotEncoder",
      "note": "competition/source identifier"
    },
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      "block": "domain",
      "type": "MultiLabelBinarizer",
      "note": "topic tags; unseen tags dropped"
    },
    {
      "block": "numeric",
      "type": "StandardScaler(with_mean=False)",
      "columns": [
        "difficulty",
        "difficulty_tier"
      ]
    }
  ],
  "feature_order": "source one-hot, then domain multi-hot, then the two scaled numeric columns",
  "split": {
    "scheme": "stratified 80/10/10",
    "seed": 42,
    "train": 3342,
    "dev": 416,
    "test": 423
  },
  "selected_hyperparameters": {
    "name": "plain_l2_c0.25",
    "class_weight": null,
    "C": 0.25
  },
  "selection": "macro-F1 then excess-token-cost on DEV only, with validation-based early stopping",
  "leakage": "features are problem metadata only: no gold answers, no correctness, no protocol outcomes, no oracle label",
  "pickled_with": {
    "note": "recorded so a loader can explain a version warning",
    "sklearn_at_fit": "1.8.0 (from the InconsistentVersionWarning emitted on load)"
  },
  "verified_in_this_environment": {
    "sklearn": "1.6.1",
    "numpy": "2.0.2",
    "scipy": "1.13.1",
    "predict": "works",
    "predict_proba": "raises AttributeError under this version; predict_example.py falls back to the decision function"
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  "root_widget_copy": {
    "path": "sklearn_model.joblib",
    "purpose": "byte-identical duplicate so Hugging Face's auto-generated sklearn snippet resolves",
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}