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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 10,
  "verdict": "Built and evaluated an accumulator-carrying MLP against the standard bench mlp_tiny on Friedman#1 regression, using the same training path, shared learning-rate sweep, and eight paired seeds. The mechanism signature was confirmed from trained-model behavior, but the accumulator had substantially higher test MSE (24.505 vs 10.594), with paired delta +13.911 and permutation p=0.0081; therefore it is a significant loss, not a win.",
  "metrics": {
    "baseline": "Friedman#1 mlp_tiny: best lr=0.006, 18 epochs; full 8-seed test MSE mean=10.593586, std=1.186041; per-seed=[9.266414,10.942157,10.532804,9.811106,9.271466,10.483624,11.298464,13.142654]; parameter count=4929.",
    "idea": "AccumulatorMLP: best among shared lr sweep at lr=0.003, 18 epochs; full 8-seed test MSE mean=24.504708, std=1.473834; per-seed=[25.353020,24.542402,26.259078,22.042612,22.800880,25.556654,23.438637,26.044382]; parameter count=7076.",
    "paired_comparison": "delta_mean=+13.911122 (idea-baseline, lower is better), idea_wins=0/8, permutation p=0.0081, verdict='idea worse (significant)'",
    "baseline_sweep": "lr=0.0015 mean=16.413998; lr=0.003 mean=13.256238; lr=0.006 mean=10.138120 on sweep seeds 0-3.",
    "idea_sweep": "lr=0.0015 mean=48.017033; lr=0.003 mean=24.504708; lr=0.006 mean=24.529536, all at 18 epochs.",
    "mechanism_signature": "Observed trained accumulator branch correction norms=[0.999964,0.999960] mean per branch, final accumulator norm=2.128705, prediction standard deviation=0.064016; confirmed=true for finite nonzero additive accumulated behavior."
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_experiment.py",
  "files": [
    "bench_experiment.py",
    "bench_report.json"
  ],
  "limitations": "Only the built-in tabular Friedman#1 track was tested; vision, sequence, dynamics, and a PDE-specific custom track were not tested. The accumulator model has a higher parameter count than mlp_tiny despite matched training conditions, and the mechanism signature verifies additive behavior rather than approximation quality or the paper's dimensional-scaling theorem.",
  "bench_report": {
    "bench_version": 1,
    "track": "tabular",
    "model": "mlp_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.006,
        "epochs": 18
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.0015,
            "epochs": 18
          },
          "mean": 16.413997888565063
        },
        {
          "cfg": {
            "lr": 0.003,
            "epochs": 18
          },
          "mean": 13.256237506866455
        },
        {
          "cfg": {
            "lr": 0.006,
            "epochs": 18
          },
          "mean": 10.138120174407959
        }
      ],
      "full": {
        "mean": 10.593586206436157,
        "std": 1.1860413365771312,
        "per_seed": [
          9.266413688659668,
          10.942156791687012,
          10.532804489135742,
          9.811105728149414,
          9.271466255187988,
          10.483624458312988,
          11.298463821411133,
          13.142654418945312
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 24.50470805168152,
      "std": 1.4738344415396776,
      "per_seed": [
        25.35301971435547,
        24.542402267456055,
        26.259077072143555,
        22.042612075805664,
        22.800880432128906,
        25.55665397644043,
        23.438636779785156,
        26.044382095336914
      ],
      "n": 8,
      "best_cfg": {
        "lr": 0.003,
        "epochs": 18
      },
      "settings": [
        {
          "cfg": {
            "lr": 0.0015,
            "epochs": 18
          },
          "mean": 48.017033100128174
        },
        {
          "cfg": {
            "lr": 0.003,
            "epochs": 18
          },
          "mean": 24.50470805168152
        },
        {
          "cfg": {
            "lr": 0.006,
            "epochs": 18
          },
          "mean": 24.52953600883484
        }
      ]
    },
    "comparison": {
      "delta_mean": 13.911121845245361,
      "idea_wins": 0,
      "n_pairs": 8,
      "per_seed_diffs": [
        16.0866060256958,
        13.600245475769043,
        15.726272583007812,
        12.23150634765625,
        13.529414176940918,
        15.073029518127441,
        12.140172958374023,
        12.901727676391602
      ],
      "p_value": 0.0081,
      "mde": 1.2874798773006364,
      "mde_rel_pct": 12.153390289290563,
      "verdict": "idea worse (significant)",
      "system_worked": false
    },
    "track_choice": "Friedman#1 is the built-in regression track and matches the idea's high-dimensional regression setting.",
    "custom_track": null,
    "parameter_counts": {
      "baseline": 4929,
      "idea": 7076
    },
    "mechanism_signature": {
      "definition": "trained accumulator behavior on tabular test predictions",
      "predicted": "context is transmitted unchanged and output corrections accumulate additively",
      "observed_mean_delta_norms": [
        0.9999635517597198,
        0.9999598488211632
      ],
      "observed_final_accumulator_norm": 2.128704696893692,
      "observed_prediction_std": 0.06401639571413398,
      "quantitative_tolerance": "nonzero branch corrections and finite accumulated state",
      "confirmed": true
    }
  },
  "system_verdict": "partial",
  "practical_verdict": "harms",
  "mechanism_ok": 1,
  "system_judged": true
}