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{
  "default": {
    "description": "ACI-Bench (Attention Clarity Index Bench): a 5,000-item diagnostic benchmark measuring whether small language models (1M\u2013150M parameters) use attention \u00d7 gradient interactions to prioritize relevant context over distractors.",
    "citation": "",
    "homepage": "",
    "license": "MIT",
    "features": {
      "id": {"dtype": "string", "_type": "Value"},
      "topic": {"dtype": "string", "_type": "Value"},
      "topicLabel": {"dtype": "string", "_type": "Value"},
      "templateId": {"dtype": "string", "_type": "Value"},
      "difficulty": {"dtype": "string", "_type": "Value"},
      "question": {"dtype": "string", "_type": "Value"},
      "referenceAnswer": {"dtype": "string", "_type": "Value"},
      "context": {"dtype": "string", "_type": "Value"},
      "segments": {"dtype": "string", "_type": "Value"},
      "relatedSegmentIds": {"dtype": "string", "_type": "Value"},
      "unrelatedSegmentIds": {"dtype": "string", "_type": "Value"},
      "keyLinkPairs": {"dtype": "string", "_type": "Value"},
      "meta": {"dtype": "string", "_type": "Value"}
    },
    "splits": {
      "test": {
        "name": "test",
        "num_bytes": 2147483,
        "num_examples": 5000,
        "dataset_name": "aci-bench"
      }
    },
    "version": "1.0.0"
  }
}