Phase-Delay Spectral Margin for Attractor RNNs / report_bench_2026-09-03T115720.md
Mechanism confirmed, baseline not beaten
Стенд-проверка (stage-2) · промт оператора:
(универсальный)
Ответ агента:
{ "worked": false, "confidence": 9, "verdict": "The phase-delay spectral-margin GRU was evaluated against the matched standard rnn_small GRU on the registered dynamics track. The intervention produced a positive trained-model stability signal, but independent task MSE was slightly worse and the paired permutation test was not significant, so this is not a benchmark win.", "metrics": { "baseline": "test MSE mean=0.000254957890319929, best lr=0.006", "idea": "test MSE mean=0.00025879375971271656, best lr=0.006; delta_mean=+0.000003835869392787572; p=0.84895" }, "bench_report": { "bench_version": 1, "track": "dynamics", "model": "rnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.006, "weight_decay": 0.0 }, "sweep": [ { "cfg": { "lr": 0.0015, "weight_decay": 0.0 }, "mean": 0.0009279211371904239 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0 }, "mean": 0.0005964032097836025 }, { "cfg": { "lr": 0.006, "weight_decay": 0.0 }, "mean": 0.0003292812507424969 } ], "full": { "mean": 0.000254957890319929, "std": 0.00010644342536032148, "per_seed": [ 0.00032660356373526156, 0.00046600779751315713, 0.00021259563800413162, 0.0003119180037174374, 0.00017991565982811153, 0.0002721373166423291, 0.0001093827813747339, 0.00016110236174426973 ], "n": 8 } }, "idea": { "mean": 0.00025879375971271656, "std": 6.582941024778054e-05, "per_seed": [ 0.00030997759313322604, 0.0002871895849239081, 0.00023464152764063329, 0.0003278508083894849, 0.00023518447414971888, 0.0002398034994257614, 0.00011388212442398071, 0.0003218204656150192 ], "n": 8 }, "comparison": { "delta_mean": 3.835869392787572e-06, "idea_wins": 3, "n_pairs": 8, "per_seed_diffs": [ -1.6625970602035522e-05, -0.00017881821258924901, 2.204588963650167e-05, 1.5932804672047496e-05, 5.526881432160735e-05, -3.233381721656769e-05, 4.499343049246818e-06, 0.00016071810387074947 ], "p_value": 0.84895, "mde": 7.921439496717511e-05, "mde_rel_pct": 31.069599323941087, "verdict": "no significant win", "system_worked": false }, "mechanism_signature": { "predicted_boundary_amplification": { "0.8": 0.9999999999999996, "1.0": 0.9999999999999999, "1.2": 1.3999999999999986 }, "observed_trained_model_mean_min_real_eigenvalue": 3.3919921815395355, "observed_trained_model_mean_max_euler_amplification": 0.6608031913638115, "confirmed": true } }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_phase_margin.py", "files": [ "bench_phase_margin.py", "bench_report.json" ], "limitations": "Only the registered built-in dynamics track was tested. The intervention uses a dense 64-by-64 eigensolver and was evaluated for 15 epochs on 1000 training and 300 test examples; larger models, longer horizons, and broader generalization were not tested.", "system_verdict": "partial", "practical_verdict": "inconclusive", "mechanism_ok": 1, "system_judged": true }