{
  "topic": "self_evolve",
  "round": 3,
  "method_name": "state-diff target router",
  "idea": "Map inferred dimensions to concrete agent-state targets: critic, planner, retriever, reranker, memory.",
  "diagnosed_issue": "Self-evolve round 3 dominant issue: scope_overgeneralization.",
  "patch_for_next_round": "Add verifier to distinguish current-story/current-arc updates from durable global user preferences.",
  "patch_source": "autodiagnosed",
  "auto_diagnosis": {
    "dominant_failure_mode": "scope_overgeneralization",
    "evidence": {
      "missed_dimensions": 5,
      "missed_targets": 5,
      "overgeneralized_scope": 5,
      "extra_dimensions": 0,
      "neutral_errors": 0
    },
    "diagnosis_text": "Self-evolve round 3 dominant issue: scope_overgeneralization.",
    "selected_next_patch": "Add verifier to distinguish current-story/current-arc updates from durable global user preferences."
  },
  "selected_next_patch": "Add verifier to distinguish current-story/current-arc updates from durable global user preferences.",
  "comparison_to_previous": {
    "status": "improved",
    "primary_metric": "target_f1",
    "primary_delta": 0.3679,
    "headline": "target_f1 changed +0.3679 vs previous round."
  },
  "failure_examples": [
    {
      "sample_id": "u_022_turn_03",
      "comment": "这段不错，继续这个张力",
      "gold_dimensions": [
        "female_agency",
        "pacing"
      ],
      "predicted_dimensions": [],
      "gold_targets": [
        "critic.checklist",
        "planner.policy",
        "reranker.policy"
      ],
      "predicted_targets": [],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=female_agency,pacing",
        "missed_targets=critic.checklist,planner.policy,reranker.policy",
        "overgeneralized_scope"
      ],
      "severity": 7.3,
      "evidence": []
    },
    {
      "sample_id": "u_032_turn_03",
      "comment": "这段不错，继续这个张力",
      "gold_dimensions": [
        "lore_density",
        "pacing"
      ],
      "predicted_dimensions": [],
      "gold_targets": [
        "critic.checklist",
        "planner.policy",
        "retriever.policy"
      ],
      "predicted_targets": [],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=lore_density,pacing",
        "missed_targets=critic.checklist,planner.policy,retriever.policy",
        "overgeneralized_scope"
      ],
      "severity": 7.3,
      "evidence": []
    },
    {
      "sample_id": "u_033_turn_10",
      "comment": "这段不错，继续这个张力",
      "gold_dimensions": [
        "female_agency",
        "pacing"
      ],
      "predicted_dimensions": [],
      "gold_targets": [
        "critic.checklist",
        "planner.policy",
        "reranker.policy"
      ],
      "predicted_targets": [],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=female_agency,pacing",
        "missed_targets=critic.checklist,planner.policy,reranker.policy",
        "overgeneralized_scope"
      ],
      "severity": 7.3,
      "evidence": []
    },
    {
      "sample_id": "u_034_turn_02",
      "comment": "这段不错，继续这个张力",
      "gold_dimensions": [
        "female_agency",
        "lore_density"
      ],
      "predicted_dimensions": [],
      "gold_targets": [
        "critic.checklist",
        "reranker.policy",
        "retriever.policy"
      ],
      "predicted_targets": [],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=female_agency,lore_density",
        "missed_targets=critic.checklist,reranker.policy,retriever.policy",
        "overgeneralized_scope"
      ],
      "severity": 7.3,
      "evidence": []
    },
    {
      "sample_id": "u_004_turn_09",
      "comment": "女主有点被动，想看她自己做决定",
      "gold_dimensions": [
        "female_agency",
        "lore_density",
        "pacing"
      ],
      "predicted_dimensions": [
        "female_agency"
      ],
      "gold_targets": [
        "critic.checklist",
        "planner.policy",
        "reranker.policy",
        "retriever.policy"
      ],
      "predicted_targets": [
        "critic.checklist",
        "memory.user",
        "reranker.policy"
      ],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=lore_density,pacing",
        "missed_targets=planner.policy,retriever.policy",
        "extra_targets=memory.user",
        "overgeneralized_scope"
      ],
      "severity": 6.65,
      "evidence": [
        "comment:agency"
      ]
    }
  ],
  "concrete_problems": [
    {
      "sample_id": "u_022_turn_03",
      "comment": "这段不错，继续这个张力",
      "gold_dimensions": [
        "female_agency",
        "pacing"
      ],
      "predicted_dimensions": [],
      "gold_targets": [
        "critic.checklist",
        "planner.policy",
        "reranker.policy"
      ],
      "predicted_targets": [],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=female_agency,pacing",
        "missed_targets=critic.checklist,planner.policy,reranker.policy",
        "overgeneralized_scope"
      ],
      "severity": 7.3,
      "evidence": []
    },
    {
      "sample_id": "u_032_turn_03",
      "comment": "这段不错，继续这个张力",
      "gold_dimensions": [
        "lore_density",
        "pacing"
      ],
      "predicted_dimensions": [],
      "gold_targets": [
        "critic.checklist",
        "planner.policy",
        "retriever.policy"
      ],
      "predicted_targets": [],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=lore_density,pacing",
        "missed_targets=critic.checklist,planner.policy,retriever.policy",
        "overgeneralized_scope"
      ],
      "severity": 7.3,
      "evidence": []
    },
    {
      "sample_id": "u_033_turn_10",
      "comment": "这段不错，继续这个张力",
      "gold_dimensions": [
        "female_agency",
        "pacing"
      ],
      "predicted_dimensions": [],
      "gold_targets": [
        "critic.checklist",
        "planner.policy",
        "reranker.policy"
      ],
      "predicted_targets": [],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=female_agency,pacing",
        "missed_targets=critic.checklist,planner.policy,reranker.policy",
        "overgeneralized_scope"
      ],
      "severity": 7.3,
      "evidence": []
    },
    {
      "sample_id": "u_034_turn_02",
      "comment": "这段不错，继续这个张力",
      "gold_dimensions": [
        "female_agency",
        "lore_density"
      ],
      "predicted_dimensions": [],
      "gold_targets": [
        "critic.checklist",
        "reranker.policy",
        "retriever.policy"
      ],
      "predicted_targets": [],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=female_agency,lore_density",
        "missed_targets=critic.checklist,reranker.policy,retriever.policy",
        "overgeneralized_scope"
      ],
      "severity": 7.3,
      "evidence": []
    },
    {
      "sample_id": "u_004_turn_09",
      "comment": "女主有点被动，想看她自己做决定",
      "gold_dimensions": [
        "female_agency",
        "lore_density",
        "pacing"
      ],
      "predicted_dimensions": [
        "female_agency"
      ],
      "gold_targets": [
        "critic.checklist",
        "planner.policy",
        "reranker.policy",
        "retriever.policy"
      ],
      "predicted_targets": [
        "critic.checklist",
        "memory.user",
        "reranker.policy"
      ],
      "predicted_scope": "global_user",
      "problems": [
        "missed_dimensions=lore_density,pacing",
        "missed_targets=planner.policy,retriever.policy",
        "extra_targets=memory.user",
        "overgeneralized_scope"
      ],
      "severity": 6.65,
      "evidence": [
        "comment:agency"
      ]
    }
  ],
  "data_eval_spec": {
    "dataset_name": "PIF-Bench synthetic novel feedback trajectories",
    "data_schema": "One row per user-turn: hidden profile, content features, explicit feedback, implicit feedback, gold preference update, gold agent-state diff, future probe.",
    "evaluation_protocol": "Run the round-specific updater on every feedback event, compare predicted dimensions/targets/scope with gold state diffs, then estimate future-probe success.",
    "metric_definitions": {
      "dimension_f1": "Macro F1 between predicted preference dimensions and gold dimensions.",
      "target_f1": "Macro F1 between predicted agent-state targets and gold targets.",
      "future_probe_win_rate": "Mean synthetic win probability on near/far/anti-overgeneralization future probes.",
      "overgeneralization_rate": "Fraction of predicted updates that incorrectly globalize local/story feedback; zero is good.",
      "neutral_no_update_accuracy": "Accuracy on neutral/no-gold-update rows; replaces the confusing no_update_precision metric."
    },
    "sample_count": 466,
    "metrics": {
      "dimension_f1": "Macro F1 between predicted preference dimensions and gold dimensions.",
      "target_f1": "Macro F1 between predicted agent-state targets and gold targets.",
      "future_probe_win_rate": "Mean synthetic win probability on near/far/anti-overgeneralization future probes.",
      "overgeneralization_rate": "Fraction of predicted updates that incorrectly globalize local/story feedback; zero is good.",
      "neutral_no_update_accuracy": "Accuracy on neutral/no-gold-update rows; replaces the confusing no_update_precision metric."
    },
    "splits": {
      "feedback_rows": 400,
      "neutral_no_update_rows": 66
    }
  },
  "metrics": {
    "round": 3,
    "dimension_f1": 0.7165,
    "target_f1": 0.6211,
    "update_target_f1": 0.6211,
    "future_probe_win_rate": 0.7061,
    "overgeneralization_rate": 0.8553,
    "feedback_incorporation_rate": 0.7775,
    "neutral_no_update_accuracy": 1.0,
    "update_rate": 0.6674
  },
  "previous_metrics": {
    "round": 2,
    "dimension_f1": 0.828,
    "target_f1": 0.2532,
    "update_target_f1": 0.2532,
    "future_probe_win_rate": 0.6635,
    "overgeneralization_rate": 0.665,
    "feedback_incorporation_rate": 0.13,
    "neutral_no_update_accuracy": 1.0,
    "update_rate": 0.8584
  },
  "metric_deltas": {
    "dimension_f1": -0.11149999999999993,
    "target_f1": 0.3679,
    "update_target_f1": 0.3679,
    "future_probe_win_rate": 0.04259999999999997,
    "overgeneralization_rate": 0.1902999999999999,
    "feedback_incorporation_rate": 0.6475,
    "neutral_no_update_accuracy": 0.0,
    "update_rate": -0.19100000000000006
  }
}