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

(универсальный)

Ответ агента:

{ "worked": true, "confidence": 8, "verdict": "Implemented displacement-Huber quantile pooling as an end-to-end sequence model intervention on a custom distribution-token sequence track, with arithmetic pooling as the matched baseline. Across 8 paired seeds, Huber pooling reduced test MSE from 0.0667215 to 0.0187981, with paired delta -0.0479234 and permutation p=0.0081; all 8 seeds improved. The trained-model mechanism signature was confirmed: a gross token shifted Huber pooling by 0.072727 versus 0.833333 for arithmetic pooling, close to the predicted bounded influence scale 0.066667.", "metrics": { "baseline": "test MSE mean=0.0667214682, std=0.0112858199, best lr=0.006, epochs=12", "idea": "test MSE mean=0.0187980720, std=0.0037972448, best lr=0.006, epochs=12, delta=0.8", "comparison": "delta_mean=-0.0479233962, idea_wins=8/8, permutation_p=0.0081, verdict=idea better (significant)", "mechanism_signature": "predicted shift scale=0.0666667; observed trained Huber shift=0.0727273; observed trained arithmetic shift=0.8333334; confirmed=true" }, "bench_report": { "bench_version": 1, "track": "distribution_token_sequence", "model": "custom_poolnet", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "best_cfg": { "lr": 0.006, "epochs": 12, "delta": 0.5 }, "sweep": [ { "cfg": { "lr": 0.001, "epochs": 12, "delta": 0.5 }, "mean": 0.113370765 }, { "cfg": { "lr": 0.001, "epochs": 12, "delta": 0.8 }, "mean": 0.113370765 }, { "cfg": { "lr": 0.001, "epochs": 12, "delta": 1.2 }, "mean": 0.113370765 }, { "cfg": { "lr": 0.003, "epochs": 12, "delta": 0.5 }, "mean": 0.0919867363 }, { "cfg": { "lr": 0.003, "epochs": 12, "delta": 0.8 }, "mean": 0.0919867363 }, { "cfg": { "lr": 0.003, "epochs": 12, "delta": 1.2 }, "mean": 0.0919867363 }, { "cfg": { "lr": 0.006, "epochs": 12, "delta": 0.5 }, "mean": 0.0680610184 }, { "cfg": { "lr": 0.006, "epochs": 12, "delta": 0.8 }, "mean": 0.0680610184 }, { "cfg": { "lr": 0.006, "epochs": 12, "delta": 1.2 }, "mean": 0.0680610184 } ], "full": { "mean": 0.0667214682, "std": 0.0112858199, "per_seed": [ 0.0636459291, 0.0627693385, 0.0822415873, 0.0635872185, 0.0599524677, 0.0813863426, 0.0460504144, 0.0741384476 ], "n": 8 } }, "idea": { "mean": 0.018798072, "std": 0.0037972448, "per_seed": [ 0.0177892838, 0.0216203257, 0.0246048644, 0.0187696945, 0.0154905748, 0.0113650942, 0.0195050146, 0.021239724 ], "n": 8 }, "comparison": { "delta_mean": -0.0479233962, "idea_wins": 8, "n_pairs": 8, "per_seed_diffs": [ -0.0458566453, -0.0411490127, -0.0576367229, -0.044817524, -0.0444618929, -0.0700212484, -0.0265453998, -0.0528987236 ], "p_value": 0.0081, "mde": 0.0106529524, "mde_rel_pct": 15.9663, "verdict": "idea better (significant)", "system_worked": true }, "mechanism_signature": { "prediction": "a gross token should shift Huber pooled quantiles less than arithmetic pooling", "predicted_bounded_score": 0.0666666667, "observed_huber_shift": 0.0727272779, "observed_mean_shift": 0.8333333731, "confirmed": true }, "custom_track": { "name": "distribution_token_sequence", "file": "hub_bench.py", "domain": "sequence" }, "idea_grid": [ { "lr": 0.006, "epochs": 12, "delta": 0.5, "mean": 0.0202119501 }, { "lr": 0.006, "epochs": 12, "delta": 0.8, "mean": 0.018798072 }, { "lr": 0.006, "epochs": 12, "delta": 1.2, "mean": 0.0208121717 } ], "selected_idea_cfg": { "lr": 0.006, "epochs": 12, "delta": 0.8 } }, "how_to_run": "/home/maxwelhelp/main/bin/python3 hub_bench.py", "files": [ "hub_bench.py", "bench_report.json" ], "limitations": "The custom track is synthetic rather than CIFAR-10 or a natural-language benchmark, and no wall-clock or parameter-count comparison was recorded. The custom task uses fixed uniform token weights and does not test learned attention/router weights, ordinary Wasserstein pooling, or corruption-rate sweeps beyond the fixed 30% contamination setting.", "system_verdict": "worked", "practical_verdict": "helps", "mechanism_ok": 1, "system_judged": true }