Robust Oscillatory RNN via Cyclic Loop-Gain Certification / bench_report.json
Mechanism confirmed, baseline not beaten
1{
2 "bench_version": 1,
3 "track": "dynamics",
4 "model": "rnn_small",
5 "metric_direction": "lower is better",
6 "n_seeds": 8,
7 "baseline": {
8 "best_cfg": {
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24 {
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31 "full": {
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44 "n": 8
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46 "idea_sweep_same_union": [
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53 {
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59 {
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80 "n": 8
81 },
82 "comparison": {
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85 "n_pairs": 8,
86 "per_seed_diffs": [
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95 ],
96 "p_value": 0.3492,
97 "mde": 7.406941029805223e-05,
98 "mde_rel_pct": 53.543844877416404,
99 "verdict": "no significant win",
100 "system_worked": false
101 },
102 "mechanism_signature": {
103 "prediction_metric": "test MSE under independent lognormal recurrent gain perturbations",
104 "baseline_gain_mse": {
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108 "0.3": 1.5009662508964539
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113 "0.15": 1.461238443851471,
114 "0.3": 1.4622179567813873
115 },
116 "predicted_effect": "cyclic loop should preserve recurrent response under small independent gains",
117 "observed_effect": "compare perturbed-vs-clean MSE ratios on trained dynamics models",
118 "confirmed": true
119 },
120 "selected_idea_cfg": {
121 "lr": 0.003
122 },
123 "protocol_notes": {
124 "structural_match": "dynamics: controlled pendulum rollout and recurrent stability",
125 "paired_seeds": [
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127 1,
128 2,
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130 4,
131 5,
132 6,
133 7
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135 "shared_architecture": "GRU(3,64)+linear head; only hidden-to-hidden topology differs",
136 "budget": {
137 "epochs": 12,
138 "batch": 128,
139 "n_train": 1200,
140 "n_test": 300
141 }
142 }
143}