target_path: coarse_rank.fusion

baseline:
  es_bias: 10.0
  es_exponent: 0.05
  text_bias: 0.1
  text_exponent: 0.35
  text_translation_weight: 1.0
  knn_text_weight: 1.0
  knn_image_weight: 2.0
  knn_tie_breaker: 0.3
  knn_bias: 0.2
  knn_exponent: 5.6
  knn_text_bias: 0.2
  knn_text_exponent: 0.0
  knn_image_bias: 0.2
  knn_image_exponent: 0.0

parameters:
  es_bias: {min: 2.0, max: 20.0, scale: log, round: 4}
  es_exponent: {min: 0.03, max: 0.28, scale: linear, round: 4}
  text_bias: {min: 0.01, max: 4.0, scale: log, round: 4}
  text_exponent: {min: 0.2, max: 1.6, scale: linear, round: 4}
  text_translation_weight: {min: 0.7, max: 1.8, scale: linear, round: 4}
  knn_text_weight: {min: 0.05, max: 1.8, scale: linear, round: 4}
  knn_image_weight: {min: 1.2, max: 6.0, scale: linear, round: 4}
  knn_tie_breaker: {min: 0.0, max: 0.4, scale: linear, round: 4}
  knn_bias: {min: 0.001, max: 2.5, scale: log, round: 4}
  knn_exponent: {min: 0.05, max: 12.0, scale: log, round: 4}
  knn_text_bias: {min: 0.001, max: 4.0, scale: log, round: 4}
  knn_text_exponent: {min: 0.0, max: 2.0, scale: linear, round: 4}
  knn_image_bias: {min: 0.01, max: 1.5, scale: log, round: 4}
  knn_image_exponent: {min: 0.0, max: 6.0, scale: linear, round: 4}

seed_experiments:
  - name: seed_low_knn_global
    description: 先验证 021002 中出现的低 knn 全局指数，去掉 reranker 后是否仍有收益。
    params:
      knn_bias: 0.6
      knn_exponent: 0.4
  - name: seed_bigset_knn_soft
    description: 从低 knn 全局指数出发，继续平滑 knn 非线性。
    params:
      text_exponent: 0.42
      text_translation_weight: 1.05
      knn_text_weight: 0.85
      knn_image_weight: 2.4
      knn_tie_breaker: 0.18
      knn_bias: 0.9
      knn_exponent: 0.18
      knn_image_exponent: 0.2
  - name: seed_bigset_knn_mid
    description: 保留平滑 knn，但让 image 通路再强一点，验证大集是否需要适度非线性。
    params:
      es_bias: 8.0
      es_exponent: 0.08
      text_bias: 0.15
      text_exponent: 0.5
      text_translation_weight: 1.15
      knn_text_weight: 0.65
      knn_image_weight: 3.1
      knn_tie_breaker: 0.12
      knn_bias: 0.45
      knn_exponent: 0.85
      knn_text_bias: 0.35
      knn_text_exponent: 0.2
      knn_image_bias: 0.22
      knn_image_exponent: 0.8
  - name: seed_bigset_text_stable
    description: 提高 lexical 区分度，观察大集是否更偏好稳健文本排序。
    params:
      es_bias: 7.0
      es_exponent: 0.12
      text_bias: 0.25
      text_exponent: 0.72
      text_translation_weight: 1.0
      knn_text_weight: 0.55
      knn_image_weight: 2.2
      knn_tie_breaker: 0.08
      knn_bias: 0.7
      knn_exponent: 0.35
      knn_text_bias: 0.5
      knn_text_exponent: 0.4
      knn_image_bias: 0.18
      knn_image_exponent: 0.35
  - name: seed_hybrid_transfer
    description: 以大集 baseline 为主，温和吸收小集历史赢家中的 image/text 强化模式。
    params:
      es_bias: 7.2
      es_exponent: 0.15
      text_bias: 0.6
      text_exponent: 0.82
      text_translation_weight: 1.28
      knn_text_weight: 0.45
      knn_image_weight: 4.0
      knn_tie_breaker: 0.08
      knn_bias: 0.2
      knn_exponent: 1.2
      knn_text_bias: 0.8
      knn_text_exponent: 0.45
      knn_image_bias: 0.3
      knn_image_exponent: 1.4
  - name: seed_legacy_bo234
    description: 直接验证 53 条集历史最优在 771 条集上的迁移表现。
    params:
      es_bias: 7.214
      es_exponent: 0.2025
      text_bias: 4.0
      text_exponent: 1.584
      text_translation_weight: 1.4441
      knn_text_weight: 0.1
      knn_image_weight: 5.6232
      knn_tie_breaker: 0.021
      knn_bias: 0.0019
      knn_exponent: 11.8477
      knn_text_bias: 2.3125
      knn_text_exponent: 1.1547
      knn_image_bias: 0.9641
      knn_image_exponent: 5.8671
  - name: seed_legacy_bo340
    description: 验证小集冠军参数在大集上是否仍有价值。
    params:
      es_bias: 5.887
      es_exponent: 0.2145
      text_bias: 4.0
      text_exponent: 1.6
      text_translation_weight: 1.4788
      knn_text_weight: 0.3693
      knn_image_weight: 5.7028
      knn_tie_breaker: 0.0174
      knn_bias: 0.0016
      knn_exponent: 12.0
      knn_text_bias: 2.6071
      knn_text_exponent: 1.0458
      knn_image_bias: 0.8282
      knn_image_exponent: 6.0
  - name: seed_image_guard
    description: 控制 image 权重但允许 image 子项指数，检查 recall 与 precision 的平衡点。
    params:
      es_bias: 9.0
      es_exponent: 0.09
      text_bias: 0.12
      text_exponent: 0.45
      text_translation_weight: 1.1
      knn_text_weight: 0.7
      knn_image_weight: 2.8
      knn_tie_breaker: 0.1
      knn_bias: 0.55
      knn_exponent: 0.55
      knn_text_bias: 0.25
      knn_text_exponent: 0.15
      knn_image_bias: 0.28
      knn_image_exponent: 1.0

optimizer:
  init_random: 2
  candidate_pool_size: 160
  explore_probability: 0.12
  local_jitter_probability: 0.62
  elite_fraction: 0.25
  min_normalized_distance: 0.08