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

(универсальный)

Ответ агента:

{
  "worked": false,
  "confidence": 9,
  "verdict": "Implemented Residual-Redundancy Adapter Clustering as a local custom multi-task regression benchmark because no built-in track contains multi-task residual coupling. The trained models recovered the true task pairs on all 8 seeds and reduced within-cluster residual TC, but MSE was marginally worse than the equal-budget shared-adapter baseline (0.39232 vs 0.39095; paired delta +0.00137; permutation p=0.22765), so there was no significant win.",
  "metrics": {
    "baseline": "Shared rank-9 adapter, lr=0.006: test MSE 0.39095 ± 0.02006 over 8 seeds.",
    "idea": "Residual-TC routed three rank-3 adapters, lr=0.006: test MSE 0.39232 ± 0.02027 over 8 seeds; paired delta +0.00137, p=0.22765. Pair recovery=1.0; mean all-task residual TC=1.30896; mean within-cluster TC=0.40378; mechanism confirmed=true."
  },
  "bench_report": {
    "bench_version": 1,
    "track": "custom_correlated_multitask_regression",
    "model": "mlp_tiny",
    "metric_direction": "lower is better",
    "n_seeds": 8,
    "baseline": {
      "best_cfg": {
        "lr": 0.006
      },
      "sweep": [
        {
          "cfg": {
            "lr": 0.001
          },
          "mean": 0.5403974950313568
        },
        {
          "cfg": {
            "lr": 0.003
          },
          "mean": 0.39297179132699966
        },
        {
          "cfg": {
            "lr": 0.006
          },
          "mean": 0.3831307291984558
        }
      ],
      "full": {
        "mean": 0.3909529335796833,
        "std": 0.020058499256199364,
        "per_seed": [
          0.3602304756641388,
          0.3643752634525299,
          0.40289655327796936,
          0.4050206243991852,
          0.420786589384079,
          "0.38486582040786743",
          0.4063948094844818,
          0.38305333256721497
        ],
        "n": 8
      }
    },
    "idea": {
      "mean": 0.3923187702894211,
      "std": 0.02027321236177226,
      "per_seed": [
        0.3610771894454956,
        0.36850693821907043,
        0.40293797850608826,
        0.4014033079147339,
        0.42628708481788635,
        0.3841452001553345,
        0.4089997410774231,
        0.38519272208213806
      ],
      "n": 8
    },
    "comparison": {
      "delta_mean": 0.0013658367097377777,
      "idea_wins": 2,
      "n_pairs": 8,
      "per_seed_diffs": [
        0.0008467137813568115,
        0.004131674766540527,
        4.1425228118896484e-05,
        -0.003617316484451294,
        0.005500495433807373,
        -0.0007206201553344727,
        0.002604931592941284,
        0.0021393895149230957
      ],
      "p_value": 0.22765,
      "mde": 0.002408680129708675,
      "mde_rel_pct": 0.6161048870139102,
      "verdict": "no measurable effect",
      "system_worked": false
    },
    "mechanism_signature": {
      "prediction": "Residual-TC clustering discovers correlated task pairs and lowers within-cluster residual dependence.",
      "predicted_mean_all_tc": 1.3089573328100736,
      "observed_mean_within_cluster_tc": 0.403780898657931,
      "pair_recovery_rate": 1.0,
      "confirmed": true
    },
    "custom_track": {
      "name": "correlated_multitask_regression",
      "file": "custom_multitask_track.py",
      "domain": "multi_task_learning"
    },
    "idea_sweep": [
      {
        "cfg": {
          "lr": 0.001
        },
        "mean": 0.5575724691152573
      },
      {
        "cfg": {
          "lr": 0.003
        },
        "mean": 0.4013301022350788
      },
      {
        "cfg": {
          "lr": 0.006
        },
        "mean": 0.3923187702894211
      }
    ]
  },
  "how_to_run": "/home/maxwelhelp/main/bin/python3 bench_run.py",
  "files": [
    "custom_multitask_track.py",
    "bench_run.py",
    "bench_report.json",
    "bench_stdout.txt"
  ],
  "limitations": "Only the custom six-task regression track was tested; no built-in vision, sequence, or dynamics track was structurally matched. The implementation uses one-time post-warmup partitioning rather than periodic reassignment or hysteresis, and does not measure memory, throughput, or a Transformer/LoRA implementation.",
  "system_verdict": "partial",
  "practical_verdict": "no_effect",
  "mechanism_ok": 1,
  "system_judged": true
}