neurips2026-anonymous/signalbench-openapps-bkp

SignalBench OpenApps Dense Signal Dataset

OpenApps browser-task evaluation points, Set-of-Marks screenshots, 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

{
  "evaluation_points": 94,
  "examples": 94,
  "ranking_candidates": 376,
  "ranking_points": 94,
  "scalar_label_values": 940,
  "state_image_references": 282,
  "trajectory_returns": 40,
  "unique_images": 64
}

Provenance

Derived from:

• https://github.com/facebookresearch/OpenApps
• https://github.com/ServiceNow/BrowserGym

Upstream license notes:

• OpenApps is CC BY-NC 4.0; this derived dataset is released as CC BY-NC 4.0.