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neurips2026-anonymous/signalbench-frozenlake-bkp

SignalBench FrozenLake Dense Signal Dataset FrozenLake 8x8 evaluation points, rendered state images, and Monte Carlo dense-signal labels under a scripted policy. This repository contains one SignalBench dataset with two synchronized views: runtime/dataset.pkl is the executable artifact used by the SignalBench benchmark code. data/examples.parquet has exactly one row per benchmark example, with state/action/next-state text, renderable state_image and next_state_image columns… See the full description on the dataset page: https://huggingface.co/datasets/neurips2026-anonymous/signalbench-frozenlake-bkp.

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SignalBench FrozenLake Dense Signal Dataset

FrozenLake 8x8 evaluation points, rendered state images, and Monte Carlo dense-signal labels under a scripted policy.

This repository contains one SignalBench dataset with two synchronized views:

—runtime/dataset.pkl is the executable artifact used by the SignalBench benchmark code.
—data/examples.parquet has exactly one row per benchmark example, with state/action/next-state text, renderable state_image and next_state_image columns when images exist, pointwise labels, and nested ranking candidates in ranking_candidates_json.
—images/, when present, contains the image files referenced by the example rows.

Ground-truth labels are Monte Carlo estimates from the GT prediction JSON files under gt/. This release includes only max-aggregated Q-value and state-value labels, including pointwise and ranking variants. The Parquet export is for inspection and metadata; use the pickle for running the benchmark with SignalBench.

Counts

json

{
  "evaluation_points": 239,
  "examples": 239,
  "ranking_candidates": 956,
  "ranking_points": 239,
  "scalar_label_values": 2390,
  "state_image_references": 1434,
  "trajectory_returns": 50,
  "unique_images": 377
}

Provenance

Derived from:

—https://github.com/Farama-Foundation/Gymnasium

Upstream license notes:

—Gymnasium is MIT.