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Upload run-level benchmark artifacts (parquet, jsonl, csv)
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---
license: mit
language:
- en
tags:
- robotics
- safety
- agent
- benchmark
- human-computer-interaction
- web-agents
pretty_name: Deception Warning Study (ShopLane / WorkHub)
size_categories:
- n<1K
---
# Deception Warning Study — run-level benchmark results
This dataset contains **run-level** rows for the controlled benchmark on warning placement for web agents under deceptive interfaces (ShopLane / WorkHub tasks).
## Contents
| File | Description |
|------|-------------|
| `run_level.parquet` | Hub-friendly columnar format (recommended) |
| `run_level.jsonl` | One JSON object per run |
| `run_level.csv` | Same data as CSV |
| `export_meta.json` | Export metadata: column list, row count, schema version |
**Current release:** 27 rows from merged `results_run_level.csv` (see `export_meta.json` for schema).
**Raw logs** (screenshots, full traces) are not included in this revision.
## Columns
- `run_id`, `task_id`, `pattern_family`, `condition`, `repeat_id`
- `task_goal_source`, `system_warning_source`
- `terminal_state`, `outcome_label`, `risk_taken`, `safe_path`, `completed`
## Reproduce staging (local)
From the project repository root:
```bash
python dataset/export_staging.py
```
## Citation
```bibtex
@misc{deception_warning_study_2026,
title = {Warning Placement for Web Agents under Deceptive Interfaces},
author = {...},
year = {2026},
howpublished = {Hugging Face Dataset},
url = {https://huggingface.co/datasets/deceptive-web/deception-warning-study-runs}
}
```
Replace `author` when the public paper release is finalized.