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

(универсальный)

Ответ агента:

{ "worked": true, "confidence": 8, "verdict": "Implemented Strongly-Rayleigh forest dropout as exact uniformly weighted K5 spanning-tree feature masks for the Friedman#1 tabular benchmark, using the same mlp_tiny architecture and training budget as Bernoulli dropout. The math check found 125 trees, mean inclusion 0.4, nonpositive pairwise covariances, and zero log-submodularity violations. On eight paired seeds, the idea achieved MSE 19.2583 versus 25.4337 for the tuned baseline, delta -6.1754 with permutation p=0.0081, so the benchmark verdict is a significant win.", "metrics": { "baseline": "Bernoulli feature dropout, tuned p in {0.30,0.40,0.50} and lr in {0.0015,0.003,0.006}; best p=0.50, lr=0.0015; 8-seed test MSE 25.4337 +/- 2.8304", "idea": "K5 spanning-tree forest masks with exactly 4/10 active features, lr=0.0015; 8-seed test MSE 19.2583 +/- 1.7862", "delta_mean": "-6.175431489944458", "permutation_p_value": "0.0081", "idea_wins": "8/8", "math": "125 spanning trees; mean inclusion 0.4; max pair covariance approximately 0; min pair covariance -0.04; 0 log-submodularity violations" }, "bench_report": { "bench_version": 1, "track": "tabular", "model": "mlp_tiny", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.0015, "p": 0.5, "epochs": 12 }, "sweep": [ { "cfg": { "lr": 0.0015, "p": 0.3, "epochs": 12 }, "mean": 39.63210868835449 }, { "cfg": { "lr": 0.0015, "p": 0.4, "epochs": 12 }, "mean": 31.991859912872314 }, { "cfg": { "lr": 0.0015, "p": 0.5, "epochs": 12 }, "mean": 24.693001747131348 }, { "cfg": { "lr": 0.003, "p": 0.3, "epochs": 12 }, "mean": 41.53972053527832 }, { "cfg": { "lr": 0.003, "p": 0.4, "epochs": 12 }, "mean": 35.30523777038574 }, { "cfg": { "lr": 0.003, "p": 0.5, "epochs": 12 }, "mean": 27.46730661392212 }, { "cfg": { "lr": 0.006, "p": 0.3, "epochs": 12 }, "mean": 47.46395492553711 }, { "cfg": { "lr": 0.006, "p": 0.4, "epochs": 12 }, "mean": 42.76505661010742 }, { "cfg": { "lr": 0.006, "p": 0.5, "epochs": 12 }, "mean": 34.259535789489746 } ], "full": { "mean": 25.43371081352234, "std": 2.830439554726994, "per_seed": [ 22.917491912841797, 27.197723388671875, 24.012426376953126, 24.644365310668945, 23.099069595336914, 32.163185119628906, 24.368993759155273, 25.066431045532227 ], "n": 8 } }, "idea": { "mean": 19.25827932357788, "std": 1.7861984392123207, "per_seed": [ 17.573183059692383, 18.7783203125, 19.6191463470459, 19.606704711914062, 17.720579147338867, 23.600263595581055, 18.389211654663086, 18.778825759887695 ], "n": 8 }, "comparison": { "delta_mean": -6.175431489944458, "idea_wins": 8, "n_pairs": 8, "per_seed_diffs": [ -5.344308853149414, -8.419403076171875, -4.393280029296875, -5.037660598754883, -5.378490447998047, -8.562921524047852, -5.9797821044921875, -6.287605285644531 ], "p_value": 0.0081, "mde": 1.2869647545735994, "mde_rel_pct": 5.060074654498938, "verdict": "idea better (significant)", "system_worked": true }, "math_check": { "num_spanning_trees": 125, "multiaffine": true, "mean_inclusion": 0.40000000000000024, "max_pair_covariance": -1.6653345369377348e-16, "min_pair_covariance": -0.0400000000000002, "negative_pairwise_dependence": true, "log_submodular_min_slack": 0.0, "log_submodular_violations": 0 }, "idea_sweep": [ { "lr": 0.0015, "result": { "mean": 19.25827932357788, "std": 1.7861984392123207, "per_seed": [ 17.573183059692383, 18.7783203125, 19.6191463470459, 19.606704711914062, 17.720579147338867, 23.600263595581055, 18.389211654663086, 18.778825759887695 ], "n": 8 } }, { "lr": 0.003, "result": { "mean": 22.983694076538086, "std": 1.943981398081157, "per_seed": [ 19.52614974975586, 22.578245162963867, 25.29038429260254, 22.89321517944336, 23.786020278930664, 26.051559448242188, 22.23059844970703, 21.51338005065918 ], "n": 8 } }, { "lr": 0.006, "result": { "mean": 25.673678874969482, "std": 3.335505365326106, "per_seed": [ 24.249820709228516, 24.600481033325195, 32.63474655151367, 27.245525360107422, 23.36638641357422, 27.80877113342285, 20.763843536107952, 24.71985626220703 ], "n": 8 } } ], "protocol_note": "Baseline Bernoulli p and all shared learning rates swept; final comparison uses eight paired seeds.", "mechanism_signature": { "predicted_max_pair_covariance": 8.23993651088983e-18, "observed_max_pair_covariance": 8.23993651088983e-18, "predicted_mean_inclusion": 0.4, "observed_mean_inclusion": 0.40000000000000024, "trained_model_output_mask_variance": 4.495115280151367, "confirmed": true } }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_forest_dropout.py", "files": [ "stage2_forest_dropout.py", "bench_report.json" ], "limitations": "Only the tabular Friedman#1 track was tested; no vision, sequence, dynamics, MoE, graph-message-passing, learned edge weights, speed/FLOP measurement, or larger forest sampler was evaluated. The negative-dependence portion of the mechanism signature is measured from the sampled masks used with trained models but is distributional rather than a learned-model output correlation; the trained-model behavioral quantity additionally recorded was output variance under forest masks.", "system_verdict": "worked", "practical_verdict": "helps", "mechanism_ok": 1, "system_judged": true }