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

(универсальный)

Ответ агента:

{ "worked": false, "confidence": 10, "verdict": "Implemented and reran the interval-zonotope reachability-loss intervention on the registered dynamics track with the shared rnn_small architecture. Across all 8 paired seeds, the idea matched the tuned baseline exactly: delta_mean=0 and permutation p=1.0. The scalar radius recurrence sanity check was exact, but no neural-network training benefit was observed.", "metrics": { "baseline": "Best config lr=0.01, weight_decay=0.0001; full mean MSE=0.0005480735380842816, std=0.00014996990905603093.", "idea": "Best config lr=0.01, weight_decay=0.0001, lambda=0.05; full mean MSE=0.0005480735380842816, std=0.00014996990905603093; paired delta=0, p=1.0." }, "bench_report": { "bench_version": 1, "track": "dynamics", "model": "rnn_small", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.01, "weight_decay": 0.0001 }, "sweep": [ { "cfg": { "lr": 0.001, "weight_decay": 0.0 }, "mean": 0.001864717691205442 }, { "cfg": { "lr": 0.001, "weight_decay": 0.0001 }, "mean": 0.0018400110420770943 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0 }, "mean": 0.0010901302302954718 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0001 }, "mean": 0.0010647484887158498 }, { "cfg": { "lr": 0.01, "weight_decay": 0.0 }, "mean": 0.0006186682076076977 }, { "cfg": { "lr": 0.01, "weight_decay": 0.0001 }, "mean": 0.0005735916565754451 } ], "full": { "mean": 0.0005480735380842816, "std": 0.00014996990905603093, "per_seed": [ 0.00046045987983234227, 0.0004709371132776141, 0.0004756892449222505, 0.0008872803882695735, 0.0004885699599981308, 0.00037048623198643327, 0.0006456486880779266, 0.0005855167983099818 ], "n": 8 }, "idea_grid": [ { "cfg": { "lr": 0.001, "weight_decay": 0.0001, "lambda": 0.05 }, "mean": 0.001864717691205442 }, { "cfg": { "lr": 0.001, "weight_decay": 0.0001, "lambda": 0.15 }, "mean": 0.001864717691205442 }, { "cfg": { "lr": 0.001, "weight_decay": 0.0001, "lambda": 0.3 }, "mean": 0.001864717691205442 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0001, "lambda": 0.05 }, "mean": 0.0010901302302954718 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0001, "lambda": 0.15 }, "mean": 0.0010901302302954718 }, { "cfg": { "lr": 0.003, "weight_decay": 0.0001, "lambda": 0.3 }, "mean": 0.0010901302302954718 }, { "cfg": { "lr": 0.01, "weight_decay": 0.0001, "lambda": 0.05 }, "mean": 0.0005735916565754451 }, { "cfg": { "lr": 0.01, "weight_decay": 0.0001, "lambda": 0.15 }, "mean": 0.0005735916565754451 }, { "cfg": { "lr": 0.01, "weight_decay": 0.0001, "lambda": 0.3 }, "mean": 0.0005735916565754451 } ] }, "idea": { "mean": 0.0005480735380842816, "std": 0.00014996990905603093, "per_seed": [ 0.00046045987983234227, 0.0004709371132776141, 0.0004756892449222505, 0.0008872803882695735, 0.0004885699599981308, 0.00037048623198643327, 0.0006456486880779266, 0.0005855167983099818 ], "n": 8 }, "comparison": { "delta_mean": 0.0, "idea_wins": 0, "n_pairs": 8, "per_seed_diffs": [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], "p_value": 1.0, "mde": 0.0, "mde_rel_pct": 0.0, "verdict": "no measurable effect", "system_worked": false }, "mechanism_signature": { "prediction": "adding the interval-zonotope loss should change the trained model task metric", "observed_nn": { "baseline_mean_test_mse": 0.0005480735380842816, "idea_mean_test_mse": 0.0005480735380842816, "observed_delta": 0.0, "best_cfg": { "lr": 0.01, "weight_decay": 0.0001, "lambda": 0.05 } }, "toy_numeric_check": { "max_radius_recurrence_error": 1.6653345369377348e-16, "confirmed": true }, "confirmed": false, "note": "The arithmetic radius recurrence is exact, but this does not establish the mechanism on the trained benchmark models." } }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py", "files": [ "stage2_bench.py", "bench_report.json", "run.log" ], "limitations": "The implementation uses an interval-box relaxation rather than full hybrid binary coupling, LP ReLU branch splitting, or exact multidimensional hybrid-zonotope constraints. The benchmark used 400 training and 200 test examples with 18 epochs; no larger-scale control benchmark or wall-clock comparison was tested.", "system_verdict": "failed", "practical_verdict": "no_effect", "mechanism_ok": 0, "system_judged": true }