Dataset: GPT-5 Kaggle Agent Traces (Gome)

This folder contains the raw parallel-trace execution logs from the Gome (GPT-5, 12 h, 1*V100) experiments reported in:

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search [Paper]

The three files here correspond to three of those traces running across 40 Kaggle competitions. Each trace records the full hypothesis → code → execution → feedback loop.

Note: These are raw per-trace logs and do not include the final multi-seed selection step (§3.6 of the paper), where top-k candidates are re-run with multiple seeds before submission. The leaderboard scores reported in the paper reflect that additional step.

JSON Structure

Each file shares the same nested structure:

{
  "<competition-name>": {
    "scenario": { ... },      ← competition description & environment
    "loop_0":   { ... },      ← first evolution loop
    "loop_1":   { ... },      ← second evolution loop
    ...
  },
  ...
}

scenario — Competition description

Metadata describing the competition environment seen by the agent before it starts.

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loop_N — One evolution iteration

Each loop corresponds to one hypothesis → code → execution → feedback cycle. Fields marked core are present in every loop; others are present in ~82–93% of loops (absent when a loop timed out or was rejected before execution).

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