Стенд-проверка (stage-2) · промт оператора:

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 9, "verdict": "Implemented spectral-certified adaptive block preconditioning with a small per-example empirical-Fisher sketch, conservative certificate-based adjacent block merging, and matched Adam baseline training on identical mlp_tiny systems. Across 8 paired seeds, the idea had much worse mean test MSE (489.45 vs 231.53), with paired delta +257.93 and permutation p=0.9404; the mechanism signature was also not confirmed because observed projected distortion was zero in this implementation. The proposed effect therefore did not transfer to this neural-network benchmark.", "metrics": { "baseline": "Best sweep config lr=0.01, epochs=1, weight_decay=0.0001; full 8-seed test MSE mean 231.5268, std 21.3007; per-seed [256.4728, 229.3470, 246.0605, 182.8064, 247.0722, 224.0730, 240.7747, 225.6076].", "idea": "Best idea config lr=0.01, epochs=1, block=64, tau=0.02, damp=0.01, sketch=3; full 8-seed test MSE mean 489.4526, std 991.4184; per-seed [29.4809, 76.0353, 67.2008, 22.4972, 3082.7842, 505.4777, 78.8188, 53.3257]. Paired delta +257.9258, p=0.9404, verdict no significant win." }, "bench_report": { "bench_version": 1, "track": "tabular", "model": "mlp_tiny", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.01, "epochs": 1, "wd": 0.0001 }, "sweep": [ { "cfg": { "lr": 0.001, "epochs": 1, "wd": 0.0 }, "mean": 236.94496 }, { "cfg": { "lr": 0.001, "epochs": 1, "wd": 0.0001 }, "mean": 236.94503 }, { "cfg": { "lr": 0.003, "epochs": 1, "wd": 0.0 }, "mean": 235.13162 }, { "cfg": { "lr": 0.003, "epochs": 1, "wd": 0.0001 }, "mean": 235.13184 }, { "cfg": { "lr": 0.01, "epochs": 1, "wd": 0.0 }, "mean": 228.6724 }, { "cfg": { "lr": 0.01, "epochs": 1, "wd": 0.0001 }, "mean": 228.67167 } ], "full": { "mean": 231.52676, "std": 21.30066, "per_seed": [ 256.47284, 229.34703, 246.06046, 182.80635, 247.07217, 224.07295, 240.7747, 225.60756 ], "n": 8 } }, "idea": { "mean": 489.45258, "std": 991.41843, "per_seed": [ 29.48086, 76.03532, 67.20081, 22.49723, 3082.78418, 505.47769, 78.81881, 53.32572 ], "n": 8 }, "comparison": { "delta_mean": 257.92582, "idea_wins": 6, "n_pairs": 8, "p_value": 0.9404, "verdict": "no significant win", "system_worked": false }, "mechanism_signature": { "prediction": "larger cross-block certificate predicts larger observed projected Fisher spectral distortion", "predicted_values": [ 1728.5964, 1842.235, 580.0485, 667.8732, 3872.9492, 1046.0316, 1335.0322, 1300.5161 ], "observed_values": [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], "correlation": 0.0, "confirmed": false }, "idea_sweep": [ { "lr": 0.001, "mean": 228.61152 }, { "lr": 0.003, "mean": 200.81461 }, { "lr": 0.01, "mean": 48.80356 } ], "chosen_idea_cfg": { "lr": 0.01, "epochs": 1, "block": 64, "tau": 0.02, "damp": 0.01, "sketch": 3 }, "protocol_notes": "Tabular matches an optimizer/preconditioning intervention; both systems use identical mlp_tiny and paired seeds. Fisher uses a small per-example gradient sketch and block-local factors." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py", "files": [ "bench_experiment.py", "bench_report.json" ], "limitations": "This was a deliberately small MVP due to repeated autograd and dense block-factor costs: 100 training samples, 50 test samples, one epoch, three per-example gradients, 64-parameter blocks, and no wall-clock or peak-memory measurement. The certificate used conservative eta=0 rather than reliable within-block spectral interval estimates. The projected trained-model signature returned zero observed shift and should be debugged before drawing conclusions about the theorem itself; the negative result applies to this implementation and budget, not a general impossibility claim.", "system_verdict": "failed", "practical_verdict": "inconclusive", "mechanism_ok": 0, "system_judged": true }