{
  "paper": {
    "arxiv_id": "2603.19665",
    "title": "GenFacet: End-to-End Generative Faceted Search via Multi-Task Preference Alignment in E-Commerce",
    "url": "https://arxiv.org/abs/2603.19665",
    "organization": "JD.com"
  },
  "dataset": {
    "name": "MovieLens 100K",
    "users": 220,
    "items": 360
  },
  "setup": {
    "adapter": "genfacet",
    "same_split_and_candidates": true
  },
  "baseline": {
    "name": "transition + content + popularity",
    "hit_at_10": 0.10909090909090909,
    "ndcg_at_10": 0.05400546778896325,
    "fresh_hit_at_10": 0.031746031746031744,
    "head_share_at_10": 0.23772727272727273
  },
  "method": {
    "name": "genfacet core mechanism (validation blend=0.1)",
    "hit_at_10": 0.1,
    "ndcg_at_10": 0.051706534948983744,
    "fresh_hit_at_10": 0.031746031746031744,
    "head_share_at_10": 0.20318181818181819
  },
  "relative": {
    "hit_at_10_percent": -8.333333333333325,
    "ndcg_at_10_percent": -4.256852007954135,
    "fresh_hit_at_10_percent": 0.0,
    "head_share_at_10_percent": -14.531548757170173
  },
  "stages": {
    "finite_scores": 360,
    "score_std": 0.1986017079760262,
    "generative_tasks": 2,
    "preference_alignment_heads": 1
  },
  "paper_results": {
    "facet_ctr_lift_percent": 42.0,
    "user_conversion_lift_percent": 2.0
  },
  "scope": "执行论文可由公开 MovieLens 特征审计的核心计算；不复刻私有日志、生产大模型或线上服务栈。",
  "manifest_ref": "reproduction:genfacet",
  "schema_version": 2,
  "manifest": {
    "adapter_key": "genfacet",
    "arxiv_id": "2603.19665",
    "title": "GenFacet: End-to-End Generative Faceted Search via Multi-Task Preference Alignment in E-Commerce",
    "paper_url": "https://arxiv.org/abs/2603.19665",
    "track": "recommendation",
    "organization": "JD.com",
    "published": "2026-03-20",
    "code_url": null,
    "topics": [
      "e-commerce-search",
      "facet-generation",
      "preference-alignment"
    ],
    "local_code_dir": "src/auto_research/reproductions/genfacet",
    "fidelity": "core_mechanism",
    "evaluation_tier": "l2_public_dataset",
    "datasets": [
      "MovieLens 100K"
    ],
    "baseline": "transition + content + popularity",
    "metrics": [
      "hit_at_10",
      "ndcg_at_10",
      "fresh_hit_at_10",
      "head_share_at_10"
    ],
    "default_seeds": [
      42,
      43,
      44
    ],
    "budget": "220 users / 360 items; validation-only blend selection",
    "device_capabilities": [
      "cpu"
    ],
    "requires_gpu_validation": false,
    "gpu_validation_artifact": null,
    "online_evidence": [
      {
        "product": "JD.com e-commerce search",
        "metric": "Facet CTR",
        "lift_percent": 42.0,
        "traffic": "production online A/B",
        "source_url": "https://arxiv.org/html/2603.19665v1",
        "source_location": "Abstract",
        "retrieved_at": "2026-09-05"
      }
    ],
    "selection_exception": null,
    "evolve_operators": [
      "reward:facet-preference"
    ]
  },
  "provenance": {
    "created_at": "2026-09-05T03:39:12.541481+00:00",
    "code_commit": "f4c21e438142960e37630c118f2dfb2e8a674004",
    "python": "3.12.9",
    "platform": "macOS-26.5.2-arm64-arm-64bit",
    "dataset_dir": "/Users/bytedance/Documents/git_daiwk/auto-research/data",
    "dataset_fingerprint": "e66c261317a7b3179720ef3e3f5f79d7a204b135d1f217e2911b153ad2ce50a0",
    "packages": {
      "auto-research": "0.1.0",
      "numpy": "2.5.2",
      "torch": "2.13.0",
      "transformers": "5.14.1"
    },
    "artifact_path": "docs/reproductions/2603.19665-genfacet/metrics/public-seeds42-44.json"
  },
  "evaluation_protocol": {
    "tier": "l2_public_dataset",
    "tier_label": "L2 公开数据集训练",
    "seeds": [
      42,
      43,
      44
    ],
    "budget": "paper-specific",
    "formal_comparison": true,
    "claim_policy": "formal multi-seed comparison"
  },
  "seed_results": [
    {
      "paper": {
        "arxiv_id": "2603.19665",
        "title": "GenFacet: End-to-End Generative Faceted Search via Multi-Task Preference Alignment in E-Commerce",
        "url": "https://arxiv.org/abs/2603.19665",
        "organization": "JD.com"
      },
      "dataset": {
        "name": "MovieLens 100K",
        "users": 220,
        "items": 360
      },
      "setup": {
        "adapter": "genfacet",
        "same_split_and_candidates": true
      },
      "baseline": {
        "name": "transition + content + popularity",
        "hit_at_10": 0.10909090909090909,
        "ndcg_at_10": 0.05400546778896325,
        "fresh_hit_at_10": 0.031746031746031744,
        "head_share_at_10": 0.23772727272727273
      },
      "method": {
        "name": "genfacet core mechanism (validation blend=0.1)",
        "hit_at_10": 0.1,
        "ndcg_at_10": 0.051706534948983744,
        "fresh_hit_at_10": 0.031746031746031744,
        "head_share_at_10": 0.20318181818181819
      },
      "relative": {
        "hit_at_10_percent": -8.333333333333325,
        "ndcg_at_10_percent": -4.256852007954135,
        "fresh_hit_at_10_percent": 0.0,
        "head_share_at_10_percent": -14.531548757170173
      },
      "stages": {
        "finite_scores": 360,
        "score_std": 0.1986017079760262,
        "generative_tasks": 2,
        "preference_alignment_heads": 1
      },
      "paper_results": {
        "facet_ctr_lift_percent": 42.0,
        "user_conversion_lift_percent": 2.0
      },
      "scope": "执行论文可由公开 MovieLens 特征审计的核心计算；不复刻私有日志、生产大模型或线上服务栈。",
      "manifest_ref": "reproduction:genfacet",
      "seed": 42
    },
    {
      "paper": {
        "arxiv_id": "2603.19665",
        "title": "GenFacet: End-to-End Generative Faceted Search via Multi-Task Preference Alignment in E-Commerce",
        "url": "https://arxiv.org/abs/2603.19665",
        "organization": "JD.com"
      },
      "dataset": {
        "name": "MovieLens 100K",
        "users": 220,
        "items": 360
      },
      "setup": {
        "adapter": "genfacet",
        "same_split_and_candidates": true
      },
      "baseline": {
        "name": "transition + content + popularity",
        "hit_at_10": 0.10909090909090909,
        "ndcg_at_10": 0.05400546778896325,
        "fresh_hit_at_10": 0.031746031746031744,
        "head_share_at_10": 0.23772727272727273
      },
      "method": {
        "name": "genfacet core mechanism (validation blend=0.1)",
        "hit_at_10": 0.1,
        "ndcg_at_10": 0.051706534948983744,
        "fresh_hit_at_10": 0.031746031746031744,
        "head_share_at_10": 0.20318181818181819
      },
      "relative": {
        "hit_at_10_percent": -8.333333333333325,
        "ndcg_at_10_percent": -4.256852007954135,
        "fresh_hit_at_10_percent": 0.0,
        "head_share_at_10_percent": -14.531548757170173
      },
      "stages": {
        "finite_scores": 360,
        "score_std": 0.1986017079760262,
        "generative_tasks": 2,
        "preference_alignment_heads": 1
      },
      "paper_results": {
        "facet_ctr_lift_percent": 42.0,
        "user_conversion_lift_percent": 2.0
      },
      "scope": "执行论文可由公开 MovieLens 特征审计的核心计算；不复刻私有日志、生产大模型或线上服务栈。",
      "manifest_ref": "reproduction:genfacet",
      "seed": 43
    },
    {
      "paper": {
        "arxiv_id": "2603.19665",
        "title": "GenFacet: End-to-End Generative Faceted Search via Multi-Task Preference Alignment in E-Commerce",
        "url": "https://arxiv.org/abs/2603.19665",
        "organization": "JD.com"
      },
      "dataset": {
        "name": "MovieLens 100K",
        "users": 220,
        "items": 360
      },
      "setup": {
        "adapter": "genfacet",
        "same_split_and_candidates": true
      },
      "baseline": {
        "name": "transition + content + popularity",
        "hit_at_10": 0.10909090909090909,
        "ndcg_at_10": 0.05400546778896325,
        "fresh_hit_at_10": 0.031746031746031744,
        "head_share_at_10": 0.23772727272727273
      },
      "method": {
        "name": "genfacet core mechanism (validation blend=0.1)",
        "hit_at_10": 0.1,
        "ndcg_at_10": 0.051706534948983744,
        "fresh_hit_at_10": 0.031746031746031744,
        "head_share_at_10": 0.20318181818181819
      },
      "relative": {
        "hit_at_10_percent": -8.333333333333325,
        "ndcg_at_10_percent": -4.256852007954135,
        "fresh_hit_at_10_percent": 0.0,
        "head_share_at_10_percent": -14.531548757170173
      },
      "stages": {
        "finite_scores": 360,
        "score_std": 0.1986017079760262,
        "generative_tasks": 2,
        "preference_alignment_heads": 1
      },
      "paper_results": {
        "facet_ctr_lift_percent": 42.0,
        "user_conversion_lift_percent": 2.0
      },
      "scope": "执行论文可由公开 MovieLens 特征审计的核心计算；不复刻私有日志、生产大模型或线上服务栈。",
      "manifest_ref": "reproduction:genfacet",
      "seed": 44
    }
  ],
  "aggregate_metrics": {
    "dataset.users": {
      "mean": 220.0,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "dataset.items": {
      "mean": 360.0,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "baseline.hit_at_10": {
      "mean": 0.10909090909090909,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "baseline.ndcg_at_10": {
      "mean": 0.05400546778896325,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "baseline.fresh_hit_at_10": {
      "mean": 0.031746031746031744,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "baseline.head_share_at_10": {
      "mean": 0.2377272727272727,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "method.hit_at_10": {
      "mean": 0.10000000000000002,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "method.ndcg_at_10": {
      "mean": 0.051706534948983744,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "method.fresh_hit_at_10": {
      "mean": 0.031746031746031744,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "method.head_share_at_10": {
      "mean": 0.2031818181818182,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "relative.hit_at_10_percent": {
      "mean": -8.333333333333325,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "relative.ndcg_at_10_percent": {
      "mean": -4.256852007954135,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "relative.fresh_hit_at_10_percent": {
      "mean": 0.0,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "relative.head_share_at_10_percent": {
      "mean": -14.531548757170173,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "stages.finite_scores": {
      "mean": 360.0,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "stages.score_std": {
      "mean": 0.1986017079760262,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "stages.generative_tasks": {
      "mean": 2.0,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "stages.preference_alignment_heads": {
      "mean": 1.0,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "paper_results.facet_ctr_lift_percent": {
      "mean": 42.0,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    },
    "paper_results.user_conversion_lift_percent": {
      "mean": 2.0,
      "std": 0.0,
      "ci95": 0.0,
      "n": 3
    }
  }
}
